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ENGINEERING (1225 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Hybrid Journal   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 14)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 271)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 6)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 4)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 18)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 6)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 12)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 10)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 30)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 13)
Advances in Polymer Science     Hybrid Journal   (Followers: 43)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 43)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 2)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 6)
AIChE Journal     Hybrid Journal   (Followers: 32)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access   (Followers: 1)
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 17)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 18)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 1)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 4)
Applied Sciences     Open Access   (Followers: 3)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 8)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 6)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 26)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 4)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 11)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 18)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 34)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 14)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 30)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 44)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 7)
Case Studies in Thermal Engineering     Open Access   (Followers: 5)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 8)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 24)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 2)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 28)
Composite Interfaces     Hybrid Journal   (Followers: 7)
Composite Structures     Hybrid Journal   (Followers: 280)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 206)
Composites Part B : Engineering     Hybrid Journal   (Followers: 259)
Composites Science and Technology     Hybrid Journal   (Followers: 200)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Science and Engineering     Open Access   (Followers: 19)
Computers & Geosciences     Hybrid Journal   (Followers: 30)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 7)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 5)
Computers and Geotechnics     Hybrid Journal   (Followers: 11)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 33)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 8)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 43)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
Corrosion Series     Full-text available via subscription   (Followers: 6)
CT&F Ciencia, Tecnologia y Futuro     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 | Last

Journal Cover Control Engineering Practice
  [SJR: 1.354]   [H-I: 84]   [43 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0967-0661
   Published by Elsevier Homepage  [3177 journals]
  • An incipient fault detection approach via detrending and denoising
    • Abstract: Publication date: May 2018
      Source:Control Engineering Practice, Volume 74
      Author(s): Zhangming He, Yuri A.W. Shardt, Dayi Wang, Bowen Hou, Haiyin Zhou, Jiongqi Wang
      An incipient fault tends to be buried by either the process trend or the measurement noise. Fault–trend ratio (FTR) and fault–noise ratio (FNR) are two main factors that impact the detection performance. An incipient fault detection approach is proposed in this paper based on the detrending and denoising techniques. There are three main phases in this approach. First, to increase FTR, a detrending algorithm is implemented. The fault detection rate can be significantly enhanced, when the normal trend is eliminated from the testing residual. Second, to increase FNR, a denoising algorithm is realized. The residual obtained from this algorithm can avoid the incipient fault being buried by the widely oscillating noise. Therefore the fault detection performance can be further improved. Third, the new detection statistic is composed based on the two algorithms. The approach is applied to a simulated process, a satellite attitude control system process, and the Tennessee Eastman process. The comparison results show that the proposed method outperforms the traditional Hotelling method in detecting incipient faults.

      PubDate: 2018-02-26T13:43:13Z
  • Active disturbance rejection control applied to automated steering for
           lane keeping in autonomous vehicles
    • Abstract: Publication date: May 2018
      Source:Control Engineering Practice, Volume 74
      Author(s): Zhengrong Chu, Yuming Sun, Christine Wu, Nariman Sepehri
      The automated steering for lane keeping is an important technique used in the autonomous vehicles. To achieve satisfactory lane keeping performance, the steering control scheme is required to be robust against the vehicle uncertainties and the external disturbances, and be easy to be implemented. To this end, the active disturbance rejection control (ADRC) is applied to the steering controller design in this paper. The ADRC scheme estimates the vehicle uncertainties and the external disturbances in real-time and then compensates them actively. The stability analysis based on the concept of Lyapunov exponents shows that the ADRC control system is exponentially stable around the equilibrium point. Simulations under varying vehicle parameters and disturbances show that the ADRC scheme is able to keep the vehicle within the lane with maximum lateral offset of 0.1 m. Finally, the ADRC scheme is implemented on a scale vehicle. Some necessary electronic devices are installed into the scale vehicle to realize the automated steering. The comparisons between the ADRC scheme and the PID controller show that the scale vehicle controlled by the ADRC scheme performs better with maximum 0.03 m and 0.16 m lateral offsets during the straight and curved lane keeping, respectively. It is also shown that the ADRC scheme is able to perform the lane change. Since the ADRC scheme and the software developed in this paper are independent on a specific platform, they can be implemented on a full-size vehicle.

      PubDate: 2018-02-26T13:43:13Z
  • Incremental model based online dual heuristic programming for nonlinear
           adaptive control
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Ye Zhou, Erik-Jan van Kampen, Qi Ping Chu
      Dual heuristic programming has gained an increasing interest in recent years because it provides an effective process for optimal adaptive control of uncertain nonlinear systems. However, it requires an off-line stage to train a global system model from a representative model, which is often infeasible to obtain in practice. This paper presents a new and efficient approach for online self-learning control based on dual heuristic programming. This method uses a recursive least square method to online identify an incremental model of the system instead of a global system model. The presented incremental model based dual heuristic programming method can adaptively generate a near-optimal controller online without a priori information of the system dynamics or an off-line training stage. To compare the online adaptability of the conventional dual heuristic programming method and the newly proposed method, two numerical experiments are performed: an online reference tracking task and a fault-tolerant control task. The results reveal that the proposed method outperforms the conventional dual heuristic programming method in online learning capacity, efficiency, accuracy, and robustness.

      PubDate: 2018-02-26T13:43:13Z
  • Nonlinear position and stiffness Backstepping controller for a two Degrees
           of Freedom pneumatic robot
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Nicolas Herzig, Richard Moreau, Tanneguy Redarce, Frédéric Abry, Xavier Brun
      This paper presents an architecture of a 2 Degrees of Freedom pneumatic robot which can be used as a haptic interface. To improve the haptic rendering of this device, a nonlinear position and stiffness controller without force measurement based on a Backstepping synthesis is presented. Thus, the robot can follow a targeted trajectory in Cartesian position with a variable compliant behavior when disturbance forces are applied. An appropriate tuning methodology of the closed-loop stiffness and closed-loop damping of the robot is given to obtain a desired disturbance response. The models, the synthesis and the stability analysis of this controller are described in this paper. Two models are presented in this paper, the first one is an accurate simulation model which describes the mechanical behavior of the robot, the thermodynamics phenomena in the pneumatic actuators, and the servovalves characteristics. The second model is the model used to synthesize the controller. This control model is obtained by simplifying the simulation model to obtain a MIMO strict feedback form. Finally, some simulation and experimental results are given and the controller performances are discussed and compared with a classical linear impedance controller.

      PubDate: 2018-02-26T13:43:13Z
  • Hierarchical nonlinear optimization-based controller of a continuous strip
           annealing furnace
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): S. Strommer, M. Niederer, A. Steinboeck, A. Kugi
      Continuous strip annealing furnaces are complex multi-input multi-output nonlinear distributed-parameter systems. They are used in industry for heat treatment of steel strips. The product portfolio and different materials to be heat-treated is steadily increasing and the demands on high throughput, minimum energy consumption, and minimum waste have gained importance over the last years. Designing a furnace control concept that ensures accurate temperature tracking under consideration of all input and state constraints in transient operations is a challenging task, in particular in view of the large thermal inertia of the furnace compared to the strip. The control problem at hand becomes even more complicated because the burners in the different heating zones of the considered furnace can be individually switched on and off. In this paper, a real-time capable optimization-based hierarchical control concept is developed, which consists of a static optimization for the selection of an operating point for each strip, a trajectory generator for the strip velocity, a dynamic optimization routine using a long prediction horizon to plan reference trajectories for the strip temperature as well as switching times for heating zones, and a nonlinear model predictive controller with a short prediction horizon for temperature tracking. The mass flows of fuel and the strip velocity are the basic control inputs. The underlying optimization problems are transformed to unconstrained problems and solved by the Gauss–Newton method. The performance of the proposed control concept is demonstrated by an experimentally validated simulation model of a continuous strip annealing furnace at voestalpine Stahl GmbH, Linz, Austria.
      Graphical abstract image

      PubDate: 2018-02-26T13:43:13Z
  • Accuracy–simplicity trade-off for small-scale helicopter models: A
           comparative study based on flight data
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Emmanuel Roussel, Vincent Gassmann, Edouard Laroche
      A good model is a trade-off between simplicity of the model structure and accuracy of the prediction. Higher accuracy is generally expected from more complex models, but at the cost of higher computational burden, more complex handling and potential identifiability issues. Depending on the targeted use, assumptions and simplifications are made to find the simplest model still capturing the important phenomena. These choices are not straightforward and, to this end, the paper gives a comparison of miniature helicopter models often found in the literature. The contribution of the paper is thus twofold. A time-domain identification procedure for parametric models of miniature helicopters is first described and applied to four different models with increasing complexity. The procedure is based on flight data obtained during a manual slow-speed flight. Secondly, the accuracies of these models are evaluated and compared, which highlights the main differences and improvements brought by the differences in the aerodynamic model equations and allows the selection of a relevant model structure depending on the target application.

      PubDate: 2018-02-26T13:43:13Z
  • Extended Kalman filter for fouling detection in thermal power plant
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Anitha Kumari Sivathanu, Srinivasan Subramanian
      A model based on-line foul monitoring approach for a power plant reheater is proposed. Dual Extended Kalman Filter (DEKF) is designed to estimate the model parameters that influence fouling. Based on the estimated parameters the performance index (Cleanliness Factor) is obtained to retrieve the extent of fouling on reheater. The simulation and experimental validation using power plant data shows the efficacy of DEKF over conventional Joint-EKF (JEKF) in estimating the model parameters. The outcome of the work will assist in soot blow scheduling for reheater by perceiving the fall in cleanliness factor and will also help in analysing its impact on heat transfer efficiency.

      PubDate: 2018-02-26T13:43:13Z
  • Digital state-feedback control of an interleaved DC–DC boost converter
           with bifurcation analysis
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): G. Gkizas, C. Yfoulis, C. Amanatidis, F. Stergiopoulos, D. Giaouris, C. Ziogou, S. Voutetakis, S. Papadopoulou
      This paper evaluates several state-feedback control design methods for a multi-phase interleaved DC–DC boost converter with an arbitrary number of legs. The advantages of state-feedback control laws are numerous since they do not burden the system with the introduction of further zeros or poles that may lead to poorer performance as far as overshoot and disturbance rejection is concerned. Both static and dynamic full state-feedback control laws are designed based on the converter’s averaged model. Building on previous work, this paper introduces significant extensions on the investigation of several undesirable bifurcation phenomena. In the case of static state-feedback it is shown that interleaving can give rise to more severe bifurcation phenomena, as the number of phases is increased, leading to multiple equilibria. As a remedy, a bifurcation analysis procedure is proposed that can predict the generation of multiple equilibria. The novelty of this paper is that this analysis can be integrated into the control design so that multiple equilibria can be completely avoided or ruled out of the operating region of interest. The proposed control laws are digitally implemented and validated in a 2-leg case study using both simulation and experimentation.

      PubDate: 2018-02-26T13:43:13Z
  • Experimental validation of attitude and rate-sensor bias filter using
           range-difference measurements
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Erlend K. Jørgensen, Thor I. Fossen, Ingrid Schjølberg, Paulo T.T. Esperança
      This paper considers the problem of constructing a filter for estimating attitude and rate-sensor bias, that has both proven stability and close-to-optimal performance with respect to noise. The filter is based on measuring the difference in time of arrival for signals sent from three or more known, fixed positions to two or more receivers on the vehicle. An inertial measurement unit is also used, both rate-sensor and accelerometer measurements, and a position estimate is needed, generated from depth and time of arrival measurements. The vectors between receivers on the vehicle are assumed to be known in the body frame, and are calculated in the inertial frame through an algebraic transformation. These vectors are used as input for a non-linear observer along with rate-sensor and accelerometer data, estimating Euler angles and rate-sensor bias. These estimates are used as a linearization point for a Linearized Kalman Filter, taking the full non-linear system into account. Two experiments are run, and the filter is compared to an Extended Kalman Filter, and a non-implementable Linearized Kalman Filter using the true state as linearization point.

      PubDate: 2018-02-26T13:43:13Z
  • An experimental comparison of PID autotuners
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Josefin Berner, Kristian Soltesz, Tore Hägglund, Karl Johan Åström
      In this paper two novel autotuners are compared with two industrially available ones. The aim is to see if the research frontline can improve the industry standard of today. Experiments are made on three laboratory processes with different characteristics. Two lag-dominated processes of which one is a level control problem with fast dynamics, and one a temperature control problem with slow dynamics, as well as one delay-dominated level control process. Both the experiments and the obtained controller performances are evaluated and discussed. The results show that the performance of the state-of-the-art industrial autotuners can be significantly improved.

      PubDate: 2018-02-26T13:43:13Z
  • Model-free fault detection and isolation of a benchmark process control
           system based on multiple classifiers techniques—A comparative study
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Hasan Abbasi Nozari, Sina Nazeri, Hamed Dehghan Banadaki, Paolo Castaldi
      This paper presents a combined data-driven framework for fault detection and isolation (FDI) based on the ensemble of diverse classification schemes. The proposed FDI scheme is configured in series and parallel forms in the sense that in series form the decision on the occurrence of fault is made in FD module, and subsequently, the FI module coupled to the FD module will be activated for fault indication purposes. On the other hand, in parallel form a single module is employed for FDI purposes, simultaneously. In other words, two separate multiple-classifiers schemes are presented by using fourteen various statistical and non-statistical classification schemes. Furthermore, in this study, a novel ensemble classification scheme namely blended learning (BL) is proposed for the first time where single and boosted classifiers are blended as the local classifiers in order to enrich the classification performance. Single-classifier schemes are also exploited in FDI modules along with the ensemble-classifier methods for comparison purposes. In order to show the performance of proposed FDI method, it was also tested and validated on DAMADICS actuator system benchmark. Besides, comparative study with the related works done on this benchmark is provided to show the pros and cons of the proposed FDI method.

      PubDate: 2018-02-26T13:43:13Z
  • Sliding mode voltage control of boost converters in DC microgrids
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Michele Cucuzzella, Riccardo Lazzari, Sebastian Trip, Simone Rosti, Carlo Sandroni, Antonella Ferrara
      This paper deals with the design of a robust decentralized control scheme for voltage regulation in boost-based DC microgrids. The proposed solution consists of the design of a suitable manifold on which voltage regulation is achieved even in presence of unknown load demand and modeling uncertainties. A second order sliding mode control is used to constrain the state of the microgrid to this manifold by generating continuous control inputs that can be used as duty cycles of the power converters. The proposed control scheme has been theoretically analyzed and validated through experiments on a real DC microgrid.

      PubDate: 2018-02-26T13:43:13Z
  • Finite control set model predictive control scheme of four-switch
           three-phase rectifier with load current observer
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Lisi Tian, Jin Zhao, Dehong Zhou
      Three-phase rectifier is typically realized by six power switches. However, this rectifier is fault sensitive in power switches. To enable continued controllable operation, the grid phase with fault rectifier leg can be connected to center tap of the dc-link capacitors, known as the four-switch three-phase rectifier (FSTPR), using hardware reconfiguration. However, the symmetry of three-phase currents and reliable operation of the FSTPR cannot be retained due to the offset of the two-capacitor voltages. This paper proposes a finite control set model predictive control (FCS-MPC) to obtain the balanced three-phase current with the offset of two-capacitor voltages suppressed. The PI-Controller-free FCS-MPC with a second-order Luenberger observer is adopted to improve the dynamic performance of FSTPR. The performance of the proposed control scheme is illustrated by extensive simulation and experimental results. The comparison with the conventional voltage-oriented-control, which is based on PI controller and pulse width modulation (PWM), is also presented to show the superiority of the proposed FCS-MPC.

      PubDate: 2018-02-26T13:43:13Z
  • Autonomous vehicle control using a kinematic Lyapunov-based technique with
           LQR-LMI tuning
    • Abstract: Publication date: April 2018
      Source:Control Engineering Practice, Volume 73
      Author(s): Eugenio Alcala, Vicenç Puig, Joseba Quevedo, Teresa Escobet, Ramon Comasolivas
      This work proposes the control of an autonomous vehicle using a Lyapunov-based technique with a LQR-LMI tuning. Using the kinematic model of the vehicle, a non-linear control strategy based on Lyapunov theory is proposed for solving the control problem of autonomous guidance. To optimally adjust the parameters of the Lyapunov controller, the closed loop system is reformulated in a linear parameter varying (LPV) form. Then, an optimization algorithm that solves the LQR-LMI problem is used to determine the controller parameters. Furthermore, the tuning process is complemented by adding a pole placement constraint that guarantees that the maximum achievable performance of the kinematic loop could be achieved by the dynamic loop. The obtained controller jointly with a trajectory generation module are in charge of the autonomous vehicle guidance. Finally, the paper illustrates the performance of the autonomous guidance system in a virtual reality environment (SYNTHIA) and in a real scenario achieving the proposed goal: to move autonomously from a starting point to a final point in a comfortable way.

      PubDate: 2018-01-10T08:21:59Z
  • Canonical variable analysis and long short-term memory for fault diagnosis
           and performance estimation of a centrifugal compressor
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Xiaochuan Li, Fang Duan, Panagiotis Loukopoulos, Ian Bennett, David Mba
      Centrifugal compressors are widely used for gas lift, re-injection and transport in the oil and gas industry. Critical compressors that compress flammable gases and operate at high speeds are prioritized on maintenance lists to minimize safety risks and operational downtime hazards. Identifying incipient faults and predicting fault evolution for centrifugal compressors could improve plant safety and efficiency and reduce maintenance and operation costs. This study proposes a dynamic process monitoring method based on canonical variable analysis (CVA) and long short-term memory (LSTM). CVA was used to perform fault detection and identification based on the abnormalities in the canonical state and the residual space. In addition, CVA combined with LSTM was used to estimate the behavior of a system after the occurrence of a fault using data captured from the early stages of deterioration. The approach was evaluated using process data obtained from an operational industrial centrifugal compressor. The results show that the proposed method can effectively detect process abnormalities and perform multi-step-ahead prediction of the system’s behavior after the appearance of a fault.

      PubDate: 2018-01-10T08:21:59Z
  • A simulation and control model for building energy management
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Maria Pia Fanti, Agostino Marcello Mangini, Michele Roccotelli
      This paper deals with the energy consumption management problem in buildings by modeling and controlling the main electric appliances. Renewable energies are taken into account by considering the production schedules of both wind and solar sources. Each appliance is described by modular mathematical models by means of the Matlab/Simulink software. A simulator is designed that models the load energy consumptions and helps to recognize how they contribute to peak demand. Moreover, a controller to manage the load usage is designed in a Petri Net framework. In the proposed control strategy, the comfort conditions are respected for each appliances on the basis of the user preferences. Finally, a real case study validates and tests the effectiveness of the simulator applied to the considered appliances.

      PubDate: 2018-01-10T08:21:59Z
  • Closed-loop identification for plants under model predictive control
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Ali Esmaili, Jianyi Li, Jinyu Xie, Joshua D. Isom
      Model predictive controllers incorporate step response models for pairings of independent and dependent variables. Motivated by the fact that it may be time-consuming to conduct open-loop experiments to identify the step response models, the paper assesses the performance of closed-loop system identification on MPC-equipped plants, using both simulated and actual plant data. Pure feedback closed-loop system identification is shown to be effective for an identifiable simulated system and an industrial hydrogen production plant. The use of closed-loop system identification as a mechanism for monitoring model quality in MPC implementations may enhance the long-term sustainability of the implementation.

      PubDate: 2018-01-10T08:21:59Z
  • Large feedback control design with limited plant information
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Robert L. Cloud, John F. O’Brien
      A novel method is presented that provides a novel, large feedback design with adequate stability margins without a plant model. First, a PID controller is found using on-line tuning. Next, the closed-loop transient response of the PID system is used to define a bandwidth, and the PID compensator transfer function is used to determine the plant gain and heuristically estimate the plant slope at crossover. Then, these parameters are used to find the compensator. A prefilter is designed to improve transient response, and adjustments are suggested for plants possessing feedback-limiting dynamics. Analytical examples and experimental data illustrate the approach’s efficacy.

      PubDate: 2018-01-10T08:21:59Z
  • Development of a upper-limb exoskeleton robot for refractory construction
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Ho Yu, Il Seop Choi, Kyung-Lyong Han, Jae Yeon Choi, Goobong Chung, Jinho Suh
      In this paper, a novel 7-DOF (degree-of-freedom) upper-limb robotic exoskeleton was developed for helping refractory construction operations in furnaces. The exoskeleton is the dual-arm type wearable robot that cooperates with human operators. Each arm includes Force/Torque (F/T) sensors to detect the human’s motion, and the robot can handle a refractory of up to 50 kg. The exoskeleton robot generates not only high strength but also various 3-dimensional motions with the load, and it is highly suitable for the refractory construction operation.

      PubDate: 2017-12-26T21:51:08Z
  • Constant power load stabilization
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Henrik Mosskull
      Stabilization of constant power loads (CPLs) fed through poorly damped input LC filters involves a trade-off between well damped filter quantities and small generated power modifications, where power modifications in general may be generated by internal CPL power control or by additional hardware. To simplify this trade-off, an explicit controller expression is presented, directly parameterized in terms of a damping factor. By also deriving damping factors corresponding to stabilization with minimal power modifications, tuning of stabilization becomes straight forward. Although applicable to most stabilization schemes, realization of the proposed stabilization is illustrated with an induction motor drive, using hardware-in-the-loop simulations.

      PubDate: 2017-12-26T21:51:08Z
  • Energy-optimal adaptive cruise control combining model predictive control
           and dynamic programming
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Andreas Weißmann, Daniel Görges, Xiaohai Lin
      In this paper a novel approach for energy-optimal adaptive cruise control (ACC) combining model predictive control (MPC) and dynamic programming (DP) is presented. The approach uses knowledge about a given route to precalculate a position-dependent energy-optimal speed trajectory using DP while taking information like speed limits, road slope, and travel time into account during the optimization. A simple MPC framework is used to control the traction force of the host vehicle such that the vehicle speed follows the energy-optimal speed trajectory as good as possible while ensuring safety-related constraints like distance to a preceding vehicle or speed limits. To show the benefits of the approach, a comparison of the energy consumption between the host vehicle and the preceding vehicle on the same route is performed. For the speed profile of the preceding vehicle, data from real test drives is used. Simulations show that the approach leads to a significant reduction of the energy consumption compared to the preceding vehicle on the same route. Furthermore, the simulations indicate that the approach achieves high energy savings even with a poor prediction model for the preceding car. Moreover, the approach has shown to run very fast, indicating its real-time capability.

      PubDate: 2017-12-26T21:51:08Z
  • Energy saving control in separate meter in and separate meter out control
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Guangrong Chen, Junzheng Wang, Shoukun Wang, Jiangbo Zhao, Wei Shen
      With the demand for energy efficiency in electro-hydraulic servo system (EHSS) increasing, the separate meter in and separate meter out (SMISMO) control system draws massive attention. In this paper, the SMISMO control system was decoupled completely into two subsystems by the proposed indirect adaptive robust dynamic surface control (IARDSC) method. Besides, a fast parameter estimation scheme was proposed to adapt to the parameter change for a better estimation performance. Also, a supply pressure controller with a disturbance observer and a supply flow rate controller with a grey model predictor were investigated and employed to save the power consumption. Finally, experimental results showed that the proposed IARDSC could achieve a good trajectory tracking performance with the fast parameter estimation. Meanwhile, the two energy saving techniques were validated.

      PubDate: 2017-12-26T21:51:08Z
  • State and state of charge estimation for a latent heat storage
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Tilman Barz, Dominik Seliger, Klemens Marx, Andreas Sommer, Sebastian F. Walter, Hans Georg Bock, Stefan Körkel
      A nonlinear state observer is designed for a thermal energy storage with solid/liquid phase change material (PCM). Using a physical 2D dynamic model, the observer reconstructs transient spatial temperature fields inside the storage and estimates the stored energy and the state of charge. The observer has been successfully tested with a lab-scale latent heat storage with a single pass tube bundle and the phase change material located in a shell around each tube. It turns out that the observer robustly tracks the real process data with as few as four internal PCM temperature sensors.
      Graphical abstract image

      PubDate: 2017-12-26T21:51:08Z
  • Trajectory tracking control of Skid-Steered Mobile Robot based on adaptive
           Second Order Sliding Mode Control
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Imad Matraji, Ahmed Al-Durra, Andri Haryono, Khaled Al-Wahedi, Mohamed Abou-Khousa
      This paper presents design and implementation of adaptive Second Order Sliding Mode Control (SOSMC) for a four wheels Skid-Steered Mobile Robot (SSMR). The control objective is to follow a predefined trajectory by regulating the linear and angular velocities, and in presence of external disturbance and parametric uncertainty. Adaptive Super Twisting (AST) algorithm is designed in order to build a robust controller with neglected chattering in steady state. The proposed controller is validated experimentally. The results show that the proposed controller guarantees the performance of the conventional SOSMC under external disturbance and parametric uncertainty with less chattering.

      PubDate: 2017-12-26T21:51:08Z
  • Adaptive soft sensors for quality prediction under the framework of
           Bayesian network
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Ziwei Liu, Zhiqiang Ge, Guangjie Chen, Zhihuan Song
      Soft sensor is widely used to predict quality-relevant variables which are usually hard to measure timely. Due to model degradation, it is necessary to construct an adaptive model to follow changes of the process. Adaptive models—moving windows (MW), time difference (TD), and locally weighted regression (LWR) under the framework of Bayesian network (BN) are proposed in this paper. BN shows great superiorities over other traditional methods, especially in dealing with missing data and the ability of learning causality. Furthermore, the acquisition of variances in BN makes it possible to perform fault detection, on the basis of 3-sigma criterion. A debutanizer column and CO2 absorption column are provided as two industrial examples to validate the effectiveness of our proposed techniques. In a debutanizer column, RMSE of MW-BN is decreased by 40% in comparison to MW-PLS. In a CO2 absorption column, the largest absolute prediction error of TD-BN is reduced by approximate 7% when compared with that of TD-PLS. Furthermore, about 38% improvements of prediction precision can be achieved in LW-BN in contrast to LW-PLS.

      PubDate: 2017-12-13T02:45:14Z
  • Model-based multi-component adaptive prognosis for hybrid dynamical
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Om Prakash, Arun Kumar Samantaray, Ranjan Bhattacharyya
      A bond graph model-based prognosis method for multiple components with unknown degradation patterns in a hybrid dynamical system is proposed. The traditional approach for remaining useful life prediction with single degradation model is inappropriate for hybrid systems where the dynamics changes according to operating mode. Therefore, multiple degradation models are suggested and these are adapted with new information of the degradation states of the monitored system. Sensitivity-based dynamic signature matrix is utilized for degradation hypothesis generation which provides the deviation directions of fewer hypothesized degradation parameters and thereby accelerates parameter and degradation trend estimation. The results are supported by experiments.

      PubDate: 2017-12-13T02:45:14Z
  • Internal model-based feedback control design for inversion-free
           feedforward rate-dependent hysteresis compensation of piezoelectric
           cantilever actuator
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Mohammad Al Janaideh, Micky Rakotondrabe, Isam Al-Darabsah, Omar Aljanaideh
      This study proposes a new rate-dependent feedforward compensator for compensation of hysteresis nonlinearities in smart materials-based actuators without considering the analytical inverse model. The proposed rate-dependent compensator is constructed with the inverse multiplicative structure of the rate-dependent Prandtl–Ishlinskii (RDPI) model. The study also presents an investigation for the compensation error when the proposed compensator is applied in an open-loop feedforward manner. Then, an internal model-based feedback control design is applied with the proposed feedforward compensator to a piezoelectric cantilever actuator. The experimental results illustrate that the proposed feedforward–feedback control scheme can be used in micro-positioning motion control applications to enhance the tracking performance of the piezoelectric cantilever actuator under different operating conditions.

      PubDate: 2017-12-13T02:45:14Z
  • Multiplexed extremum seeking for calibration of spark timing in a
           CNG-fuelled engine
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Jalil Sharafi, William H. Moase, Chris Manzie
      The compositional variability of many alternative fuels, coupled with fuel agnostic behaviour like engine ageing and vehicle-to-vehicle differences, leads to the desire for some form of online calibration in order to optimise fuel efficiency. This has led to the incorporation of extremum seeking techniques within the field in order to continually fine tune engine performance. These typically address steady state engine performance and are characterised by slow convergence times, hindering their deployment in typical dynamic driving scenarios. To address this potential shortcoming, in this paper a novel multiplexed extremum seeking scheme is proposed to track a time-varying extremum caused by a measurable disturbance. It consists of multiple extremum seeking agents that are individually activated based on the disturbance. The multiplexed approach accommodates the rigorous practical stability results of the “traditional” extremum seeking approaches, but offers improved results in dynamic scenarios. The proposed approach is implemented both in simulation and experimentally on a compressed natural gas (CNG) engine operating over a drive cycle. The experimental results show that under proper tuning, the proposed controller can improve the engine fuel efficiency for unknown natural gas compositions without requiring gas composition sensing at little additional calibration effort.

      PubDate: 2017-12-13T02:45:14Z
  • LPV-based power system stabilizer: Identification, control and field tests
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Fabrício Gonzalez Nogueira, Walter Barra Junior, Carlos Tavares da Costa Junior, Janio José Lana
      This paper shows the design and tests of an LPV power system stabilizer aimed at improving the damping of electromechanical oscillations in power systems. In order to capture the dynamic model for control design, LPV models were estimated from experimental data. The generator active and reactive powers were used as scheduling parameters. The control problem is formulated as a parameterized linear matrix inequality, which the positivity condition is relaxed through a sum-of-squares decomposition. The controller ensures stability and H ∞ performance for a set of operating conditions. Field tests were carried out on a 10-kVA machine and on a 350-MVA hydroelectric generator.

      PubDate: 2017-12-13T02:45:14Z
  • Variable selection for nonlinear soft sensor development with enhanced
           Binary Differential Evolution algorithm
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Le Yao, Zhiqiang Ge
      In this paper, two enhanced Binary Differential Evolution (BDE) algorithms are proposed to select variables for nonlinear process soft sensor development. Firstly, the Parallel BDE (PBDE) algorithm is presented to extract the optimal individuals of several parallel short evolution paths of basic BDE, where the spurious variables are effectively eliminated. And the most relevant variables are selected through a double-layer selection strategy with the validating Root Mean Square Error (RMSE) for evaluating criterion. Secondly, the Boosting BDE (BBDE) algorithm is proposed through applying the boosting technique to the parallel evolution paths. The performance of the previous path needs to be taken into account when conducting the current evolution path. The selected probabilities of variables are given through the weighted summation of the selection results of all paths. Also, a double-layer selection is conducted on BBDE algorithm. The feasibility and effectiveness of the proposed methods are demonstrated through a nonlinear numerical example and a real industrial process.

      PubDate: 2017-12-13T02:45:14Z
  • Disturbance-observer based control for magnetically suspended wheel with
           synchronous noise
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): Yuanjin Yu, Zhaohua Yang, Chao Han, Hu Liu
      A disturbance-observer based method is proposed to attenuate the synchronous vibration of a magnetically suspended wheel (MSW). When the rotary speed is nonzero, the synchronous vibration exists. To analyze this vibration, a precise dynamic of the MSW is researched and the synchronous vibrations model is established. A novel vibration attenuation method is proposed by combining a disturbance observer and a state-feedback method. Using Lyapunov’s stability theorem, parameters of the controller are determined. Finally, results of numerical simulations and experiments indicate that the proposed method dramatically reduces the synchronous jitter and thus significantly improves precision of the deflection angle.

      PubDate: 2017-12-13T02:45:14Z
  • Self-tuning MIMO disturbance feedforward control for active hard-mounted
           vibration isolators
    • Abstract: Publication date: March 2018
      Source:Control Engineering Practice, Volume 72
      Author(s): M.A. Beijen, M.F. Heertjes, J. Van Dijk, W.B.J. Hakvoort
      This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is implemented as a self-tuning generalized FIR filter. This filter contains a priori knowledge of the poles, such that relatively few parameters have to be estimated which makes the algorithm computationally efficient. The zeros of the filter are estimated using the filtered-error least mean squares (FeLMS) algorithm. Residual noise shaping is used to reduce bias. Conditions on convergence speed, stability, bias, and the effects of sensor noise on the self-tuning algorithm are discussed in detail. The combined control strategy is validated on a 6-DOF Stewart platform, which serves as a multi-axis and hard-mounted vibration isolation system, and shows significant improvement in the rejection of floor vibrations.

      PubDate: 2017-12-13T02:45:14Z
  • Robust fault detection with Interval Valued Uncertainties in Bond Graph
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Mayank-Shekhar Jha, Genevieve Dauphin-Tanguy, Belkacem Ould-Bouamama
      This paper describes a novel formalism for modelling uncertain system parameters and measurements, as interval models in a Bond Graph (BG) modelling framework. The main scientific interest remains in integrating the benefits of BG modelling technique and properties of Interval Analysis (IA), for efficient diagnosis of uncertain systems. Structural properties of Bond graphs in Linear Fractional transformation (BG-LFT) are exploited to model interval-valued uncertainties over a BG model in order to form an uncertain BG. The inherent causal properties are exploited to generate interval-valued fault indicators. Then, various properties of IA are used to generate point valued residual and interval-valued thresholds. The latter must contain the point valued residuals under nominal system functioning. A systematic procedure is proposed for passive-type fault detection method which is robust to uncertain system parameters and measurements. The viability of the method is shown through experimental study of a steam generator system. The limitations associated with existing fault detection method based on BG-LFT are alleviated by the proposed approach. Moreover, it is shown that proposed approach generalizes the BG-LFT method. This work forms the initial step towards integrating interval analysis based capabilities in BG framework for fault detection and health monitoring of uncertain systems.

      PubDate: 2017-12-13T02:45:14Z
  • Robust fulfillment of constraints in robot visual servoing
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Pau Muñoz-Benavent, Luis Gracia, J. Ernesto Solanes, Alicia Esparza, Josep Tornero
      In this work, an approach based on sliding mode ideas is proposed to satisfy constraints in robot visual servoing. In particular, different types of constraints are defined in order to: fulfill the visibility constraints (camera field-of-view and occlusions) for the image features of the detected object; to avoid exceeding the joint range limits and maximum joint speeds; and to avoid forbidden areas in the robot workspace. Moreover, another task with low-priority is considered to track the target object. The main advantages of the proposed approach are low computational cost, robustness and fully utilization of the allowed space for the constraints. The applicability and effectiveness of the proposed approach is demonstrated by simulation results for a simple 2D case and a complex 3D case study. Furthermore, the feasibility and robustness of the proposed approach is substantiated by experimental results using a conventional 6R industrial manipulator.

      PubDate: 2017-12-13T02:45:14Z
  • Analysis and design of time-deadbands for univariate alarm systems
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Muhammad Shahzad Afzal, Tongwen Chen, Ali Bandehkhoda, Iman Izadi
      Time-deadbands (or alarm latches) are popular alarm configuration methods used in industry to improve the alarm system performance. In this paper, time-deadband based configurations for the case of univariate alarm systems are analyzed. Mathematical models are developed based on Markov processes, and analytical expressions for performance indices (the false alarm rate, missed alarm rate, and expected detection delay) are derived. Systematic design procedures are also proposed, and the utility of the methods is illustrated through design examples.

      PubDate: 2017-12-13T02:45:14Z
  • Optimal online selection of type 1 diabetes-glucose metabolism models
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Berno J.E. Misgeld, Philipp G. Tenbrock, Eyal Dassau, Francis J. Doyle, Steffen Leonhardt
      We address an optimal experimental design (OED) procedure for the online selection of type-1-diabetes (T1D) mellitus glucose metabolistic models. A fully observable reduced-order nonlinear dynamic model is presented and subsequently parameterised for Göttingen Minipigs and patients, that were both subject to an automatic insulin delivery. A bank of continuous–discrete unscented Kalman filters (CDUKF) is designed and parameterised for Göttingen Minipigs and patients. Based on this filter bank of CDUKF, a novel online OED design procedure is developed, that is used to identify the correct parameter set out of several available sets for measured blood glucose concentrations. The procedure utilises forward model simulations to calculate optimal system inputs. This leads to the identification of the correct parameter set under arbitrary conditions. Results are presented for both subgroups.

      PubDate: 2017-12-13T02:45:14Z
  • An application of economic model predictive control to inventory
           management in hospitals
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): J.M. Maestre, M.I. Fernández, I. Jurado
      In this paper, we present experimental results from the application of model predictive control (MPC) to inventory management in a real hospital. In particular, the stock levels of ten different drugs that belong to the same laboratory have been controlled by using an MPC policy. The results obtained after four months show that the adopted approach outperforms the method employed by the hospital and reduces both the average stock levels and the work burden of the pharmacy department. This paper also paper presents some practical insights regarding the application of advanced control methods in this context.

      PubDate: 2017-12-13T02:45:14Z
  • Model-fusion-based online glucose concentration predictions in people with
           type 1 diabetes
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Xia Yu, Kamuran Turksoy, Mudassir Rashid, Jianyuan Feng, Nicole Hobbs, Iman Hajizadeh, Sediqeh Samadi, Mert Sevil, Caterina Lazaro, Zacharie Maloney, Elizabeth Littlejohn, Laurie Quinn, Ali Cinar
      Accurate predictions of glucose concentrations are necessary to develop an artificial pancreas (AP) system for people with type 1 diabetes (T1D). In this work, a novel glucose forecasting paradigm based on a model fusion strategy is developed to accurately characterize the variability and transient dynamics of glycemic measurements. To this end, four different adaptive filters and a fusion mechanism are proposed for use in the online prediction of future glucose trajectories. The filter fusion mechanism is developed based on various prediction performance indexes to guide the overall output of the forecasting paradigm. The efficiency of the proposed model fusion based forecasting method is evaluated using simulated and clinical datasets, and the results demonstrate the capability and prediction accuracy of the data-based fusion filters, especially in the case of limited data availability. The model fusion framework may be used in the development of an AP system for glucose regulation in patients with T1D.

      PubDate: 2017-12-13T02:45:14Z
  • High-accuracy robotized industrial assembly task control schema with force
           overshoots avoidance
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Loris Roveda, Nicola Pedrocchi, Manuel Beschi, Lorenzo Molinati Tosatti
      The presented paper proposes an analytical force overshoots free control architecture for standard industrial manipulators involved in high-accuracy industrial assembly tasks (i.e., with tight mounting tolerances). As in many industrial scenarios, the robot manipulates components through (compliant) external grippers and interacts with partially unknown compliant environments. In such a context, a force overshoot may result in task failures (e.g., gripper losses the component, component damages), representing a critical control issue. To face such problem, the proposed control architecture makes use of the force measurements as a feedback (obtained using a force/torque sensor at the robot end-effector) and of the estimation of the equivalent interacting elastic system stiffness (i.e., force sensor– compliant gripper–compliant environment equivalent stiffness) defining two control levels: (i) an internal impedance controller with inner position and orientation loop and (ii) an external impedance shaping force tracking controller. A theoretical analysis of the method has been performed. Then, the method has been experimentally validated in an industrial-like assembly task with tight mounting tolerances (i.e., H7/h6 mounting). A standard industrial robot (a Universal Robot UR 10 manipulator) has been used as a test-platform, equipped with an external force/torque sensor Robotiq FT 300 at the robot end-effector and with a Robotiq Adaptive Gripper C-Model to manipulate target components. ROS framework has been adopted to implement the proposed control architecture. Experimental results show the avoidance of force overshoots and the achieved target dynamic performance.

      PubDate: 2017-12-13T02:45:14Z
  • Practical dynamic matrix control for thermal power plant coordinated
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Un-Chul Moon, Youngjun Lee, Kwang Y. Lee
      This paper proposes three practical strategies for the coordinated control (CC) of a thermal power plant using dynamic matrix control (DMC) that can be directly applied to industrial power plants. The three strategies are the replacement of conventional CC using DMC, the inclusion of disturbance variables, and a supplementary reference correction of the conventional CC. The performance during wide range operation of the three DMC–CCs is compared and discussed with the simulation results of a large-scale power plant model.

      PubDate: 2017-12-13T02:45:14Z
  • Iterative Pole–Zero model updating: A combined sensitivity approach
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): M. Dorosti, R.H.B. Fey, M.F. Heertjes, H. Nijmeijer
      A crucial step in the control of a weakly damped high precision motion system is having an accurate dynamic model of the system from actuators to sensors and to the unmeasured performance variables. A (reduced) Finite Element (FE) model may be a good candidate apart from the fact that it often does not sufficiently match with the real system especially when it comes to machine-to-machine variation. To improve the dynamic properties of the FE model toward the dynamic properties of a specific machine, an Iterative Pole–Zero (IPZ) model updating procedure is used that updates numerical poles and zeros of Frequency Response Functions (FRFs) toward measured poles and zeros, which can be extracted from the measured FRFs. It is assumed that in a practical situation, the model (physical) parameters that cause discrepancy with the real structure are unknown. Therefore, the updating parameters will be the eigenvalues of the stiffness and/or damping (sub)matrix. In this paper, an IPZ model updating is introduced which combines the sensitivity functions of both poles and zeros (with respect to the corresponding updating parameters) together with the cross sensitivity functions between poles and zeros. The procedure is verified first using simulated experiments of a pinned-sliding beam structure and then using non-collocated FRF measurement results from a cantilever beam setup.

      PubDate: 2017-12-13T02:45:14Z
  • Performance improvement of an NCS closed over the internet with an
           adaptive Smith Predictor
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Ana Paula Batista, Fábio G. Jota
      In this paper, the potential improvement in performance of an NCS (Networked Control System) subject to variable delays controlled by means of an adaptive system is analyzed. An adaptive Smith Predictor has been used to compensate the effects of varying delays measured on the network. The NCS, closed over the Internet, has been implemented using a platform called NCS-CMUF, composed of local and remote stations. The plant used to carry out the experimental tests is consisted of an optical oven in which the luminosity loop is the main controlled variable whose time constant lies in the range of milliseconds. This paper highlights the importance of synchronization between the clocks of the local and remote stations to perform consistent measurements of network delays, in order to provide an active compensation of the effects of delays. The results show the effectiveness of adaptive Smith Predictor in coping with different delays and the performance improvements achieved with the proposed scheme.

      PubDate: 2017-11-16T16:01:45Z
  • Computation of eco-driving cycles for Hybrid Electric Vehicles:
           Comparative analysis
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): D. Maamria, K. Gillet, G. Colin, Y. Chamaillard, C. Nouillant
      In this paper, the calculation of eco-driving cycles for a Hybrid Electric Vehicle (HEV), using Dynamic Programming (DP), is investigated from the complexity-solving method viewpoint. The study is based on a comparative analysis of four optimal control problems formulated using distinct levels of modeling. Starting with three state dynamics (vehicle position and speed, battery state-of-charge) and three control variables (engine and electric machine torque, gear-box ratio), the number of state variables is reduced to two in a first simplification. The other two simplifications are based on decoupling the optimization of the control variables into two steps: an eco-driving cycle is calculated assuming that the vehicle is propelled only by the engine. Then, knowing that the vehicle follows the eco-driving cycle calculated in the first step, an off-line energy management strategy (torque split) for an HEV is calculated to split the requested power at the wheels between the electric source and the engine. As is shown, the decreased complexity and the decoupling optimization lead to a sub-optimality in fuel economy while the computation time is noticeably reduced. Quantitative results are provided to assess these observations.

      PubDate: 2017-11-16T16:01:45Z
  • Parallel distributed compensation for improvement of level control in
           carbonization column for soda production
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Snejana Yordanova, Milen Slavov, Branimir Gueorguiev
      The liquid level control is essential in many production installations but the classic approaches often fail to ensure the desired performance. The reasons are the plant nonlinearity, the level oscillations and the plant model uncertainties. The aim of the present investigation is to improve the existing linear control of the level in the carbonization columns for soda ash production by employing fuzzy logic using parallel distributed compensation (PDC). The design of the PDC is based on a nonlinear Takagi–Sugeno–Kang (TSK) plant model which is derived via genetic algorithms optimization and validated using the data from the real time linear level control. The PDC control performs soft blending of the outputs of several parallel local linear controllers each developed for the local linear plant of the TSK model. The fuzzy rules are represented by ordinary logics conditions to enable the PDC programming and use by an industrial programmable logic controller. The PDC increases the dynamic accuracy in the level control and reduces the frequency of the control oscillations compared to the previous linear control thus prolonging the lifetime of the expensive pneumatic actuators used.
      Graphical abstract image

      PubDate: 2017-11-16T16:01:45Z
  • Applicability of available Li-ion battery degradation models for system
           and control algorithm design
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Xing Jin, Ashish Vora, Vaidehi Hoshing, Tridib Saha, Gregory Shaver, Oleg Wasynczuk, Subbarao Varigonda
      Within electrified vehicle powertrains, lithium-ion battery performance degrades with aging and usage, resulting in a loss in both energy and power capacity. As a result, models used for system design and control algorithm development would ideally capture the impact of those efforts on battery capacity degradation, be computationally efficient, and simple enough to be used for algorithm development. This paper provides an assessment of the state-of-the-art in lithium-ion battery degradation models, including accuracy, computational complexity, and amenability to control algorithm development. Various aging and degradation models have been studied in the literature, including physics-based electrochemical models, semi-empirical models, and empirical models. Some of these models have been validated with experimental data; however, comparisons of pre-existing degradation models across multiple experimental data sets have not been previously published. Three representative models, a 1-d electrochemical model (a combination of performance model and degradation model), a semi-empirical degradation model (the performance is predicted by an equivalent circuit model) and an empirical degradation model (the performance is predicted by an equivalent circuit model), are compared against four published experimental data sets for a 2.3-Ah commercial graphite/LiFePO 4 cell. Based on simulation results and comparisons to experimental data, the key differences in the aging factors captured by each of the models are summarized. The results show that the physics-based model is best able to capture results across all four representative data sets with an error less than 10%, but is 20 x slower than the empirical model, and 134 x slower than the semi-empirical model, making it unsuitable for powertrain system design and model-based algorithm development. Despite being computationally efficient, the semi-empirical and empirical models, when used under conditions that lie outside the calibration data set, exhibit up to 71% error in capacity loss prediction. Such models require expensive experimental data collection to recalibrate for every new application. Thus, in the author’s opinion, there exists a need for a physically-based model that generalizes well across operating conditions, is computationally efficient for model-based design, and simple enough for control algorithm development.

      PubDate: 2017-11-08T15:25:35Z
  • Constrained nonlinear filter for vehicle sideslip angle estimation with no
           a priori knowledge of tyre characteristics
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Salvatore Strano, Mario Terzo
      The vehicle sideslip angle is one of the most functional feedbacks for the actual control systems of vehicle dynamics. The measurement of the sideslip angle is expensive and unsuitable for common vehicles. Consequently, its estimation is nowadays an important task. This paper focuses on the vehicle sideslip angle estimation adopting a constrained unscented Kalman filter (CUKF) that takes into account state constrains during the estimation process. State boundaries are useful in real-world applications to prevent unphysical results and to improve the estimator robustness. The proposed technique fully takes into account the measurement noise and nonlinearities. A vehicle model with single track has been adopted for the design of the estimator. Simulations have been carried out and comparisons with the unscented Kalman filter (UKF) are illustrated. Performance of the estimators have been checked through the application to experimental data. The results show the goodness of the CUKF, able to give an estimate fully in accordance with the measurement. Moreover, the results show that the CUKF, due to the presence of the boundaries, outperforms the UKF.

      PubDate: 2017-11-08T15:25:35Z
  • Bringing probabilistic analysis capability from planning to operation
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Yousu Chen, Pavel Etingov, Erin Fitzhenry, Poorva Sharma, Tony Nguyen, Yuri Makarov, Mark Rice, Craig Allwardt, Steve Widergren
      The dynamic behavior of smart grid technologies requires the transition from a deterministic to a probabilistic control paradigm. This necessitates a smoother, better-integrated interplay between the functional roles of planning and operations to leverage the capabilities of probabilistic analysis in both realms. This paper presents two power system probabilistic analysis tools and how they are integrated into the GridOPTICS Software System (GOSS), a middleware platform facilitating deployment of new applications for the future power grid. Case study results show the developed tools provide better prediction of the power system balancing requirements, better transmission congestions management, and better system reliability.

      PubDate: 2017-11-08T15:25:35Z
  • Model predictive control for offset-free reference tracking of fractional
           order systems
    • Abstract: Publication date: February 2018
      Source:Control Engineering Practice, Volume 71
      Author(s): Sotiris Ntouskas, Haralambos Sarimveis, Pantelis Sopasakis
      In this paper an offset-free model predictive control scheme is presented for fractional-order systems using the Grünwald–Letnikov derivative. The infinite-history fractional-order system is approximated by a finite-dimensional state-space system and the modeling error is cast as a bounded disturbance term. Using a state observer, it is shown that the unknown disturbance at steady state can be reconstructed and modeling errors and other persistent disturbances can be attenuated. The effectiveness of the proposed controller–observer ensemble is demonstrated in the optimal administration of an anti-arrhythmic medicine with fractional-order pharmacokinetics.

      PubDate: 2017-11-08T15:25:35Z
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