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ENGINEERING (1204 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: 6)
AASRI Procedia     Open Access   (Followers: 15)
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: 230)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
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: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 7)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 15)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 25)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 28)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 37)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 1)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 4)
AIChE Journal     Hybrid Journal   (Followers: 30)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
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: 16)
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: 7)
Annals of Science     Hybrid Journal   (Followers: 7)
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: 12)
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: 7)
Applied Network Science     Open Access  
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 7)
Arid Zone Journal of Engineering, Technology and Environment     Open Access   (Followers: 2)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
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: 8)
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: 4)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
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: 3)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access  
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 9)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 32)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 3)
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  
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: 3)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 14)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 41)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 3)
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: 6)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal  
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: 21)
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: 3)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
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: 26)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 254)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 179)
Composites Part B : Engineering     Hybrid Journal   (Followers: 230)
Composites Science and Technology     Hybrid Journal   (Followers: 171)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 14)
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: 6)
Computer Science and Engineering     Open Access   (Followers: 17)
Computers & Geosciences     Hybrid Journal   (Followers: 28)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 5)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 10)
Computing and Visualization in Science     Hybrid Journal   (Followers: 5)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 30)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 6)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 8)
Control Engineering Practice     Hybrid Journal   (Followers: 42)
Control Theory and Informatics     Open Access   (Followers: 7)
Corrosion Science     Hybrid Journal   (Followers: 25)
CT&F Ciencia, Tecnologia y Futuro     Open Access  
CTheory     Open Access  

        1 2 3 4 5 6 7 | Last

Journal Cover Control Engineering Practice
  [SJR: 1.354]   [H-I: 84]   [42 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0967-0661
   Published by Elsevier Homepage  [3043 journals]
  • Vehicle sideslip estimation: A kinematic based approach
    • Abstract: Publication date: October 2017
      Source:Control Engineering Practice, Volume 67
      Author(s): Donald Selmanaj, Matteo Corno, Giulio Panzani, Sergio M. Savaresi
      This paper deals with vehicle sideslip angle estimation. The paper introduces an industrially amenable kinematic-based approach that does not need tire–road friction parameters or other dynamical properties of the vehicle. The convergence of the estimate is improved by the introduction of a heuristic based on readily available inertial measurements. The method is tested on a vast collection of tests performed in different conditions, showing a satisfactory behavior despite not using any information on the road friction. The extensive experimental validation confirms that the estimate is robust to a wide range of driving scenarios.

      PubDate: 2017-08-03T16:58:10Z
  • Secure and private control using semi-homomorphic encryption
    • Abstract: Publication date: October 2017
      Source:Control Engineering Practice, Volume 67
      Author(s): Farhad Farokhi, Iman Shames, Nathan Batterham
      Networked control systems with encrypted sensors measurements is considered. Semi-homomorphic encryption, specifically the Paillier encryption, is used so that the controller can perform the required computation on the encrypted data. Conditions on the parameters of the encryption technique are provided that guarantee the stability and the performance of the closed-loop system. The results are subsequently extended Laplacian based distributed systems, such as formation-seeking algorithms. It is shown that the problem of figuring out the state measurements of the neighbouring agents of a compromised agent upon using the proposed algorithm is numerically intractable.

      PubDate: 2017-08-03T16:58:10Z
  • Dominant trend based logistic regression for fault diagnosis in
           nonstationary processes
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Jun Shang, Maoyin Chen, Hongquan Ji, Donghua Zhou, Haifeng Zhang, Mingliang Li
      This paper presents a fault diagnosis method called dominant trend based logistic regression (DTLR) for monitoring nonstationary processes. Different from conventional sample-wise diagnosis approaches, it uses sliding windows to collect process data and extract dominant trend features. After data preprocessing via robust sparse representation, the feature vector reflecting variation trend is obtained by solving a convex optimization problem, i.e., dominant trend extraction (DTE). Then the ℓ 2 -norm of the dominant trend vector is used as a detection index to quantify the dissimilarity between normal and abnormal conditions. Once it exceeds the control limit, the feature vector is used to train the weight vector of logistic regression. The fault type can be determined as the class with the maximum conditional probability. With trend information, DTLR can effectively detect and isolate faults in nonstationary processes. Simulations on a synthetic nonstationary dynamic process, a nonstationary continuous stirred tank reactor (CSTR), and the real data of a blast furnace iron-making process illustrate superior monitoring and isolation performance of DTLR, compared with conventional methods.

      PubDate: 2017-08-03T16:58:10Z
  • FIR filter-based online jerk-constrained trajectory generation
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Pierre Besset, Richard Béarée
      In the context of human–robot manipulation interaction for service or industrial robotics, the robot controller must be able to quickly react to unpredictable events in dynamic environments. In this paper, a FIR filter-based trajectory generation methodology is presented, combining the simplicity of the analytic second-order trajectory generation, i.e. acceleration-limited trajectory, with the flexibility and computational efficiency of FIR filtering, to generate on the fly smooth jerk-constrained trajectories. The proposed methodology can generate synchronized (fixed-time) and time-optimal jerk-limited trajectories from arbitrary initial velocity and acceleration conditions within 20 microsecond. Other jerk-constrained trajectories such as jerk-time fixed trajectories, which are particularly suitable for vibration reduction, can be easily generated. Experimental validations carried out on a seven axis Kuka LBR iiwa are presented.

      PubDate: 2017-08-03T16:58:10Z
  • A quadratic boundedness approach to robust DC motor fault estimation
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Mariusz Buciakowski, Marcin Witczak, Marcin Mrugalski, Didier Theilliol
      In the paper, a novel methodology of actuator fault estimation for linear discrete-time systems is proposed. To solve such a challenging problem, a quadratic boundedness approach is used to guarantee the convergence of the proposed state and actuator fault estimation method. In the proposed methodology, the robustness is achieved through the unknown input decoupling while an unappealing effect of the undecoupled disturbances is minimized. Moreover, the developed approach enables to obtain a feasible set of joint system state and fault estimation error. Based on this knowledge, a novel methodology of calculating the uncertainty intervals of the system state and actuator fault is proposed. The illustrative part of the paper presents results obtained for the laboratory DC servo-motor and compares the proposed approach with two alternative methods. Based on this real-data example, the efficiency of the developed methodology is clearly exposed.

      PubDate: 2017-08-03T16:58:10Z
  • UAS based Li-ion battery model parameters estimation
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): D. Ali, S. Mukhopadhyay, H. Rehman, A. Khurram
      Estimation of Lithium-ion (Li-ion) battery model parameters is key for accurately determining battery state of charge (SOC). Estimating these parameters requires substantial experimental effort. This work reduces the experimentation required, by using universal adaptive stabilization (UAS) for estimating parameters appearing in battery model state equations. Accuracy of estimated model parameters is verified by comparing the estimated and measured battery terminal voltage. SOC obtained using the estimated model parameters, and open circuit EMF vs SOC curve, captures effects due to discharge currents of small magnitude, which Coulomb counting, well known filtering methods ignore. Rigorous mathematical analysis supports the experimental results presented.

      PubDate: 2017-07-23T14:15:10Z
  • Inverse dynamics based robust control method for position commanded servo
           actuators in robot manipulators
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Nabanita Adhikary, Chitralekha Mahanta
      In this paper, a simple torque to position conversion method is proposed for position commanded servo actuators used in robot manipulators. The torque to position conversion is based on the low level controller of the servomotor. The proposed conversion law is combined with a backstepping sliding mode control method to realize a robust dynamic controller. The proposed torque based method can control a servomotor which can otherwise be operated only through position inputs. This method facilitates dynamic control for position controlled servomotors and it can be extended to position commanded robotic manipulators also. Simulation and experimental studies are conducted to validate the proposed torque to position conversion based robust control method.

      PubDate: 2017-07-23T14:15:10Z
  • Complete dynamic model of the Twin Rotor MIMO System (TRMS) with
           experimental validation
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Azamat Tastemirov, Andrea Lecchini-Visintini, Rafael M. Morales-Viviescas
      In this paper we develop a complete dynamic model of the Twin Rotor MIMO System (TRMS) using the Euler–Lagrange method. Our model improves upon the model provided by the manufacturer in the user manual and upon previous models of the TRMS which can be found in the literature. The complete procedure for the model parameters’ estimation and validation is illustrated.

      PubDate: 2017-07-12T12:42:45Z
  • Fault-tolerant model predictive control of a direct methanol-fuel cell
           system with actuator faults
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): R. Keller, S.X. Ding, M. Müller, D. Stolten
      This paper investigates fault tolerant model predictive control (MPC) of a direct methanol fuel cell (DMFC) system with several faults in the methanol feeding pump. An active FTMPC strategy with a hierarchal structural design is developed. The focus here is on fault detection and isolation (FDI) and the implementation of fault-tolerant strategies within the control algorithm. To this end, a model-based FDI scheme with virtual sensors is first developed by means of the real-time diagnosis of fault occurrence during operation. Thereby, several faults in the methanol pump are characterized and the information integrated into the MPC algorithm in each fault case. Strategies are presented to reconfigure the active fault-tolerant MPC to keep the DMFC system stable in case of a feeding failure. Moreover, economic, stability and lifetime characteristics are also integrated into the active fault-tolerant MPC. The proposed FDI and FTMPC scheme is tested experimentally in a DMFC test rig with a 5-cell DMFC stack to demonstrate the effectiveness and robustness of the designed approach. Several fault scenarios with the FTMPC are shown. Particularly in the case of fuel cells, fault tolerance is necessary to meet the goals of long-lasting system stability and efficiency.

      PubDate: 2017-07-12T12:42:45Z
  • Further results on nonlinear tracking control and parameter estimation for
           induction motors
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): C.M. Verrelli, P. Tomei, E. Lorenzani, R. Fornari, F. Immovilli
      The original contribution of this paper, which concerns induction motors with uncertain constant load torque and rotor/stator resistances, is twofold. The first innovative contribution relies on the experimental analysis of the latest theoretically-based sensorless/output feedback solutions to the problem of tracking rotor speed and flux modulus reference signals with the simultaneous estimation of the uncertain parameters. The second novel contribution is constituted by the proof of existence for a new adaptive local flux observer from rotor speed and stator currents/voltages, which, in its full-order or reduced-order-like versions, involves neither over-parameterizations nor non-a priori verifiable first order stator resistance identifiability conditions at steady-state.

      PubDate: 2017-07-12T12:42:45Z
  • Contents list
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65

      PubDate: 2017-07-12T12:42:45Z
  • Experimental validation of an active heave compensation system:
           Estimation, prediction and control
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): M. Richter, S. Schaut, D. Walser, K. Schneider, O. Sawodny
      This work presents a comprehensive active heave compensation (AHC) approach proposing estimation, prediction and control methods. The estimation concept covers the estimation of the attitude using sensor fusion as well as the estimation of heave which is obtained by applying adaptive filtering methods. Moreover, a prediction approach based on a Levinson recursive least squares (RLS) algorithm is proposed. The actuation concept consists of a model predictive trajectory planner and a model-based Two-Degree-of-Freedom (2-DOF) controller. It is based on a model of the hydraulically driven compensation winch. The overall compensation performance as well as the estimation and prediction accuracy are evaluated using a full-scale AHC test bench.

      PubDate: 2017-07-03T08:31:21Z
  • Robust control for disturbed buck converters based on two GPI observers
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Zuo Wang, Shihua Li, Junxiao Wang, Qi Li
      The output voltage tracking problem of a disturbed buck converter is investigated in this paper via a GPI observer-based approach. Control performances of the converters are always influenced by undesirable effects of disturbances. These disturbances usually are of time-varying forms. Conventional backstepping schemes cannot achieve satisfactory performances in handling time-varying disturbances. By adding integral actions into the controller, only the slow-varying disturbances are asymptotically compensated in this way. In this paper, two GPI observers are constructed to estimate the lumped time-varying disturbances. By introducing the disturbance estimations into the design process, a composite GPI observer-based robust control scheme is developed. The proposed algorithm performs a promising disturbance rejection ability. Rigorous stability is guaranteed. Experimental results in the presence of time-varying disturbances are illustrated to show the feasibility of the proposed composite method.

      PubDate: 2017-07-03T08:31:21Z
  • Control of technological and production processes as distributed parameter
           systems based on advanced numerical modeling
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): G. Hulkó, C. Belavý, K. Ondrejkovič, L. Bartalský, M. Bartko
      The paper describes some practical control problems of technological and production processes as nonlinear distributed parameter systems. These are solved based on advanced numerical modeling in virtual software environments offered for the numerical dynamic analysis of technological and production processes with co-simulations. The controlled systems are interpreted as nonlinear lumped input and distributed parameter output systems. Synthesis of control in space relation is solved by approximation methods in temporal relation by methods of control of lumped parameter systems. Some results are demonstrated by the control of the secondary cooling in the continuous casting of steel, based on a software sensor. Furthermore, the control of a casting die preheating process is introduced in this framework using a programmable logic controller (PLC).

      PubDate: 2017-07-03T08:31:21Z
  • Application of Valuation-Based Systems for the availability assessment of
           systems under uncertainty
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Siqi Qiu, Mohamed Sallak, Walter Schön, Zohra Cherfi-Boulanger
      The aim of the paper is twofold. First, it proposes an original application of the Valuation-Based System (VBS) for the availability assessment of systems under uncertainty in a time-varying fashion. Uncertainties related to failure data of components (data uncertainty) and the system structure (model uncertainty) are analysed in the proposed model. Second, it proposes the application of the VBS for the availability assessment of the European Rail Traffic Management System (ERTMS) Level 2 under uncertainty according to the railway dependability standards. The originality of this work lies in the application of the VBS for the availability assessment of systems under data and model uncertainties, and the proposition of a temporal VBS to evaluate the instantaneous system availability.

      PubDate: 2017-07-03T08:31:21Z
  • Fault detection and diagnosis in a cement rotary kiln using PCA with
           EWMA-based adaptive threshold monitoring scheme
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Azzeddine Bakdi, Abdelmalek Kouadri, Abderazak Bensmail
      This paper presents main results of fault detection and diagnosis in a cement manufacturing plant using a new monitoring scheme. The scheme is based on multivariate statistical analysis and an adaptive threshold strategy. The process is statistically modeled using Principle Component Analysis (PCA). Instead of the conventional fixed control limits, adaptive thresholds are used to evaluate the common T 2 and Q statistics as faults indicators. The adaptive thresholds are computed and updated using a modified Exponentially Weighted Moving Average (EWMA) chart. These techniques are merged together to construct a novel monitoring scheme whose effectiveness is demonstrated using involuntary real fault of a cement plant process and some simulated faulty cases.

      PubDate: 2017-07-03T08:31:21Z
  • Battery state of health monitoring by estimation of the number of cyclable
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Xin Zhou, Jeffrey L. Stein, Tulga Ersal
      This paper introduces a method to monitor battery state of health (SOH) by estimating the number of cyclable Li-ions, a health-relevant electrochemical variable. SOH monitoring is critical to battery management in balancing the trade-off between maximizing system performance and minimizing battery degradation. The decrease of cyclable Li-ions indicates the effect on the SOH of degradation mechanisms that consume cyclable Li-ions. The unavailability of the number of cyclable Li-ions through non-invasive measurements makes its estimation necessary for in-situ SOH monitoring. In this paper, the extended Kalman filter (EKF) is used to estimate the number of cyclable Li-ions as an unknown battery parameter. The single particle model (SPM), a simplified battery electrochemical model, is used as the model in the EKF to achieve a computational complexity suitable for on-line estimation. Simulations are performed under typical electric vehicle current trajectories using an example parameter set for a hybrid-electric-vehicle battery. In the simulations, the battery is represented by the Doyle–Fuller–Newman (DFN) model, an electrochemical model with higher fidelity than the SPM. To comply with the practice, instead of using the same parameters as the DFN model in the SPM, parameterization of the SPM is performed before estimation of the number of cyclable Li-ions. The simulations show high estimation accuracy of the number of cyclable Li-ions using the EKF, even with the structural and parametric differences between the DFN model and the SPM, under both the ideal conditions and various non-ideal conditions (i.e., SOC estimation error, additional modeling error, and measurement noise).

      PubDate: 2017-07-03T08:31:21Z
  • Variable frequency resonant controller for load reduction in wind turbines
    • Abstract: Publication date: September 2017
      Source:Control Engineering Practice, Volume 66
      Author(s): Rafael S. Castro, Aurélio T. Salton, Jeferson V. Flores, Michel Kinnaert, Daniel F. Coutinho
      While most loads on wind turbines are originated from wind speed fluctuations, they show a periodic nature with a time-varying frequency proportional to the turbine rotation. This paper exploits this relation and proposes a modified Resonant Controller able to attenuate these frequency-varying periodic disturbances. The resulting controller is designed for both partial and full load wind speed conditions, therefore, it is able to reject periodic loads even when the wind turbine system is subject to changes in the operating rotation speed. Furthermore, a novel piecewise linear representation of the system is presented allowing a systematic design procedure, based on Linear Matrix Inequalities, in order to compute the control parameters. Simulation results in a 2 . 5 MW large scale three-bladed wind turbine illustrate the proposed method, which is able to reduce the root mean value of blade load up to 12 times when compared to a traditional LPV controller.

      PubDate: 2017-07-03T08:31:21Z
  • Development of soft sensors for permanent downhole Gauges in deepwater oil
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Luis A. Aguirre, Bruno O.S. Teixeira, Bruno H.G. Barbosa, Alex F. Teixeira, Mario C.M.M. Campos, Eduardo M.A.M. Mendes
      Downhole pressure is an important process variable in the operation of gas-lifted oil wells. The device installed in order to measure this variable is often called a Permanent Downhole Gauge (PDG). Replacing a faulty PDG is often not economically viable and to have an alternative estimate of the downhole pressure is an important goal. Using data from operating PDGs, this paper describes a number of issues dealt with in the development of soft sensors for several deepwater gas-lifted oil wells. Some of the tested models include nonlinear polynomials, neural networks, committee machines, unscented Kalman filters and filter banks. The variety of model classes used in addition to the diversity of oil wells considered brings to light some of the key-problems that have to be faced and reveal the strengths and weaknesses of each alternative solution. A major constraint throughout the work was the use of historical data, hence no specific tests were performed at any time. The aim of this work is to discuss the procedures, pros and cons of the tested solutions and to point to possible future directions of research.
      Graphical abstract image

      PubDate: 2017-07-03T08:31:21Z
  • Robust control and estimation of clutch-to-clutch shifts
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Kirti D. Mishra, K. Srinivasan
      Clutch-to-clutch shifts are ubiquitous in automatic transmissions, motivating the need for formal and robust methods for controlling these shifts. Limited sensing in production transmissions poses a severe hurdle for feedback control of these gearshifts. In the current study, nonlinear estimation methods are developed to compensate for limited sensing, and enable model-based closed loop control of the torque and inertia phases of shifts by manipulation of clutch pressures. During the torque phase, the offgoing clutch is controlled to emulate a one-way clutch, which ensures smooth coordination of the two clutches and reduced overall variation in the output shaft torque during the gearshift. During the inertia phase, the oncoming clutch is controlled to ensure smooth engagement at lock-up, resulting in reduction of shock and subsequent driveline oscillations. Controller performance is evaluated through numerical simulation of the proposed observer based controller on an experimentally validated high order model of a stepped production automatic transmission. The results show that shift control objectives were met by the proposed estimation and control strategy in the presence of appreciable model uncertainty and speed sensor noise, thus validating the robustness and practical effectiveness of the controller. Also, the proposed model-based controller was shown to be effective in controlling gearshifts at different power-levels (at different throttle openings), which establishes effectiveness of the same over a wide range of operating conditions.

      PubDate: 2017-07-03T08:31:21Z
  • A sparse dissimilarity analysis algorithm for incipient fault isolation
           with no priori fault information
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Chunhui Zhao, Furong Gao
      The conventional multivariate statistical process control (MSPC) methods in general quantify the distance between the new sample and the modelling samples for fault detection and diagnosis, which, however, do not check the changes of data distribution as long as monitoring statistics stay inside normal region enclosed by control limit and thus are not sensitive to incipient changes. In the present work, a sparse dissimilarity (SDISSIM) algorithm is developed which can isolate the incipient abnormal variables that change the data distribution structure and does not need any priori fault knowledge. First, the distribution dissimilarity is decomposed deeply and significant dissimilarity is extracted to integrate the critical difference of variable covariance structure between the reference normal operation distribution and the actual distribution. Second, a sparse regression-based optimization problem is formulated to isolate abnormal variables associated with changes of distribution structure. Sparse coefficients are obtained with only a small fraction of variables’ coefficients nonzeros, pointing to abnormal variables. As illustrations, SDISSIM is applied to both simulated and real industrial process data with encouraging results to figure out the slight distortions.

      PubDate: 2017-06-22T08:08:18Z
  • A direct power control for DFIG under a three phase symmetrical voltage
           sag condition
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): J.S. Solís-Chaves, Mariana Silva Barreto, Mauricio B.C. Salles, Valdemir Martins Lira, Rogerio V. Jacomini, Alfeu J. Sguarezi Filho
      In this paper, a novel direct power control algorithm for a Doubly Fed Induction Generator-based wind system, robust to the machine parameters variations, is projected. The proposed scheme employs two loops designed using the discretized equations of the generator to obtain a high performance of the controller. Also, the rotor voltage vector is computed by the proposed strategy in order to guarantee the DFIG operation even during a symmetrical voltage sag on the power grid. The influence of the estimation errors for these parameters was also researched. The results obtained by computer simulations and by experimental setup corroborate the proposed controller performance.

      PubDate: 2017-06-16T07:39:15Z
  • Stability and performance of current harmonic controllers for multiphase
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Jussi Karttunen, Samuli Kallio, Jari Honkanen, Pasi Peltoniemi, Pertti Silventoinen
      Multiphase electric machines can provide significant benefits over conventional three-phase machines. A drawback to multiphase machines is that they are known to have problems with stator current harmonics. The harmonics can be eliminated by various current harmonic control methods. However, there appears to be no clear agreement on the most suitable method for multiphase machines. This paper aims to compare different current harmonic controllers in terms of stability and performance under model uncertainty. A detailed theoretical analysis of the harmonic controllers is given by taking a modern multi-input multi-output approach based on a structured singular value analysis. Further, the performance of the harmonic controllers is studied with experimental results from a dual three-phase permanent magnet synchronous machine. The analysis and results of this paper show how to design robust high-performance current harmonic controllers for multiphase machines.

      PubDate: 2017-06-16T07:39:15Z
  • Robust guaranteed cost ILC with dynamic feedforward and disturbance
           compensation for accurate PMSM position control
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Slawomir Mandra, Krzysztof Galkowski, Harald Aschemann
      This contribution presents a robust ILC control design based on guaranteed costs. By combining this ILC design with dynamic feedforward control and an observer-based disturbance compensation, the initial tracking errors in an early learning stage can be reduced. The benefits of the proposed design approach are pointed out at the example of a robust position control of a Permanent Magnet Synchronous Motor (PMSM), which is subject to uncertain model parameters. The paper is concluded with convincing experimental results from a dedicated test rig. Moreover, a comparison with a classical observer-based tracking control is provided.

      PubDate: 2017-06-12T07:31:57Z
  • Contents list
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64

      PubDate: 2017-06-07T07:22:14Z
  • Observer based robust integral sliding mode load frequency control for
           wind power systems
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Yanliang Cui, Lanlan Xu, Minrui Fei, Yubin Shen
      This paper investigates the load frequency control (LFC) for wind power systems with modeling uncertainties and variant loads. Since the system state is difficult to be accurately measured due to perturbation of nonlinear load, an observer is designed for reconstructing a substitution system state. Afterwards, an integral sliding surface is designed and a sliding mode LFC (SMLFC) strategy is proposed for reducing frequency deviations of the overall power system. Remarkably, it has been pointed out that a larger convergence rate of the observer error system has positive influences on the SMLFC performances, while the larger observer gain deteriorates the dynamic behavior. For seeking an acceptable balance so as to determine the optimal controller parameters, a collaborative design algorithm is proposed. The proposed method not only guarantees the asymptotical stability of overall power systems but also capable of improving the system robustness. Numerical examples are provided to demonstrate the effectiveness of the proposed methods.

      PubDate: 2017-06-02T02:47:07Z
  • Indirect NOx emission monitoring in natural gas fired boilers
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Timo Korpela, Pekka Kumpulainen, Yrjö Majanne, Anna Häyrinen, Pentti Lautala
      New emission regulations will increase the need for inexpensive NO x emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NO x emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of <3% in all cases), generalizability and simplicity. Therefore, the approach fulfils the requirements of the Industrial Emission Directive and is valid to be applied as a soft sensor in PEMS 1 1 Predictive Emission Monitoring System. applications in practise. However, each boiler model should be identified individually.

      PubDate: 2017-06-02T02:47:07Z
  • Adaptive feedforward control of exhaust recirculation in large diesel
    • Abstract: Publication date: August 2017
      Source:Control Engineering Practice, Volume 65
      Author(s): Kræn Vodder Nielsen, Mogens Blanke, Lars Eriksson, Morten Vejlgaard-Laursen
      Environmental concern has led the International Maritime Organization to restrict NO x emissions from marine diesel engines. Exhaust gas recirculation (EGR) systems have been introduced in order to comply to the new standards. Traditional fixed-gain feedback methods are not able to control the EGR system adequately in engine loading transients so alternative methods are needed. This paper presents the design, convergence proofs and experimental validation of an adaptive feedforward controller that significantly improves the performance in loading transients. First the control concept is generalized to a class of first order Hammerstein systems with sensor delay and exponentially converging bounds of the control error are proven analytically. It is then shown how to apply the method to the EGR system of a two-stroke crosshead diesel engine. The controller is validated by closed loop simulation with a mean-value engine model, on an engine test bed and on a vessel operating at sea. A significant reduction of smoke formation during loading transients is observed both visually and with an opacity sensor.

      PubDate: 2017-06-02T02:47:07Z
  • Transformation of GRAFCET to PLC code including hierarchical structures
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Robert Julius, Max Schürenberg, Frank Schumacher, Alexander Fay
      GRAFCET is an advantageous modelling language for the specification of controllers in discrete event systems. It allows for hierarchically structuring a control program's specification based on the elements enclosing steps, partial-Grafcets and forcing orders. A method is already available for the automatic transformation of Grafcets 1 1 “GRAFCET” (in capital letters) refers to the standard and the modelling language in general, whereas a “Grafcet” is a particular model, i.e. one control specification. into PLC code but this method cannot keep the hierarchical structures due to limitations of the PLC language SFC. In this contribution a systematic approach to automatically transform Grafcets into PLC code while retaining the hierarchical structures is described.

      PubDate: 2017-05-28T02:30:29Z
  • Adaptive backstepping control for an engine cooling system with guaranteed
           parameter convergence under mismatched parameter uncertainties
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): S. Butt, H. Aschemann
      This paper proposes a novel adaptive backstepping control for a special class of nonlinear systems with both matched and mismatched unknown parameters. The parameter update laws resemble a nonlinear reduced-order disturbance observer. Thus, the convergence of the estimated parameter values to the true ones is guaranteed. In each recursive design step, only single parameter update law is required in comparison to the existing standard adaptive backstepping techniques based on overparametrization and tuning functions. To make a fair comparison with the overparametrization and tuning function methods, a second-order nonlinear engine cooling system is taken as a benchmark problem. This system is subject to both matched and mismatched state-dependent lumped disturbances. Moreover, the proposed model-based controllers are compared with a classical PI control by using performance metrics, i.e., root-mean-square error and control effort. The comparative analysis based on these performance metrics, simulations as well as experiments highlights the effectiveness of the proposed novel adaptive backstepping control in terms of asymptotic tracking, global stability and guaranteed parameter convergence.

      PubDate: 2017-05-28T02:30:29Z
  • Cause-effect analysis of industrial alarm variables using transfer
    • Abstract: Publication date: Available online 20 May 2017
      Source:Control Engineering Practice
      Author(s): Wenkai Hu, Jiandong Wang, Tongwen Chen, Sirish L. Shah
      A method is proposed to analyze cause-effect relationships among binary-valued alarm variables. A normalized transfer entropy (NTE) and a normalized direct transfer entropy (NDTE) are formulated as basic statistical metrics, with consideration of two specific characteristics of alarm variables, namely, random delays and mutual independence among alarm occurrences. A modified statistical test is developed to determine significance thresholds of NTEs and NDTEs, based on which the cause-effect relationships can be inferred. The effectiveness of the proposed method is illustrated via numerical and industrial case studies.

      PubDate: 2017-05-23T02:04:06Z
  • Taylor series expansion based repetitive controllers for power converters,
           subject to fractional delays
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): R. Nazir
      Digital repetitive controllers are widely employed to track/reject the periodic signals with zero steady-state error. Their implementation involves the use of single or multiple digital delay elements. Practically, the delay element is implemented by the use of memory locations, where samples are held and released after a specific number of sampling periods, equivalent to the desired time delay. A problem arises when the desired time delay becomes a non-integer multiple of the sampling time. Such time delays can be accurately realized by employing a fractional delay filter This paper presents a Taylor Series expansion based digital repetitive controller designed to implement any (integer, non-integer) delay in the control of power converters, occurring due to uncontrollable variations in the reference frequency. The T3644aylor Series expansion transforms the fractional delay filter design problem to a differentiator/sub-filter design. Finite impulse response (FIR) and infinite impulse response (IIR) fractional delay (FD) filter concepts can be applied to realize the required fractional delay. This structure provides efficient on-line tuning capabilities i.e. FD can easily generate any required fractional delay without redesigning the filter when the delay parameter varies. An example is demonstrated to show the effectiveness of this approach, for a single-phase power inverter feeding a passive load.

      PubDate: 2017-05-13T07:48:26Z
  • Structural analysis based sensor measurement fault diagnosis in cement
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): V. Gomathi, Seshadhri Srinivasan, K. Ramkumar, Guruprasath Muralidharan
      This investigation presents a fault diagnosis methodology for detecting sensor faults in cement industries pyro processing section. It works in three steps: (a) modelling, (b) analysis, and (c) validation. In the modelling, the actual data from the cement pyro processing is used to do a correlation analysis between output and input variables. The structural model is obtained from the correlation tests. During the analysis phase the Structural analysis Tool (SaTool) is used to detect the detectability and isolability of the faults. The results of the structural analysis are validated in a cement industry using residual analysis performed using structural sensor model and real-time measurements. The main advantages of this fault diagnosis technique are: (a) it requires only correlation analysis to obtain the structural model without a detailed physical model as in other methods, (b) conclusions regarding detectability and isolability can be easily drawn during the analysis stage itself, and (c) the method is simple compared to the model-based, and data-history based methods. The effectiveness of the proposed method is illustrated using data from cement pyro processing plant and its performance is compared with model based approaches for four different types of sensor faults: (1) bias, (2) drift, (3) stuck, and (4) measurement failures. Our results demonstrate that the structural method is able to detect the sensor faults even in the presence of noisy information, and its performance is comparable with that of model based approaches without employing a physical model.

      PubDate: 2017-05-13T07:48:26Z
  • Robustification of the modular tracking control system for non-Standard
           N-Trailers of uncertain kinematics
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Maciej Marcin Michałek, Marcin Kiełczewski
      The paper is devoted to the problem of control performance robustification for the modular cascade-like tracking controller, recently devised for the N-Trailer vehicles equipped solely with off-axle hitching (called the non-Standard N-Trailers). It has been shown that the control performance degradation due to parametric uncertainty of the N-Trailer kinematics can be treated as an effect of an external input-matched disturbance acting on the closed-loop system dynamics. One proposes to suppress this detrimental effect by redesigning of the original cascade-like tracking controller combining it with an additional disturbance observation-compensation loop. It is revealed under which conditions the new robustified control law guarantees uniform ultimate boundedness of tracking errors for arbitrarily small ultimate bounds. Forecasts of a theoretical analysis have been validated by numerical examples and practically verified with a laboratory-scale three-trailer robotic vehicle. The results illustrate control performance improvement achievable with the new robust controller, even in the case of substantial parametric uncertainty of a vehicle model.

      PubDate: 2017-05-13T07:48:26Z
  • Stabilization of perturbed system via IMC: An application to load
           frequency control
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Sahaj Saxena, Yogesh V. Hote
      This paper proposes a robust controller for a parametric uncertain system of order three. The scheme conceptualizes the approach of selecting the worst-case plant and then the controller is designed using the internal model control principle which constitutes the reduced model of worst-case plant. The beauty of the proposed approach is that even though the plant is uncertain, the complete robust stability analysis and controller design is carried out by a single linear model. As an illustrative example, a load frequency control (LFC) problem is considered for single- and multi-area power systems in presence of unexpected disturbances, parametric uncertainties and physical constraints. The proposed controller is also applied to the network topology similar to standard IEEE 39 bus system (New England 10 machine test system) to validate the more realistic LFC application. Simulation studies show that the proposed controller brings robust and fast disturbance rejection attributes.

      PubDate: 2017-05-08T08:10:17Z
  • A multi-objective iterative learning control approach for additive
           manufacturing applications
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Ingyu Lim, David J. Hoelzle, Kira L. Barton
      Iterative learning control (ILC) is a method for improving the performance of stable, repetitive systems. Standard ILC is constructed in the temporal domain, with performance improvements achieved through iterative updates to the control signal. Recent ILC research focuses on reformulating temporal ILC into the spatial domain, where 2D convolution accounts for spatial closeness. This work expands spatial ILC to include optimization of multiple performance metrics. Performance objectives are classified into primary, complementary, competing, and domain specific objectives. New robustness and convergence criteria are provided. Simulation results validate flexibility of the spatial framework on a high-fidelity additive manufacturing system model.

      PubDate: 2017-05-08T08:10:17Z
  • Nonlinear model predictive control of a batch fluidized bed dryer for
           pharmaceutical particles
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Francis Gagnon, André Desbiens, Éric Poulin, Pierre-Philippe Lapointe-Garant, Jean-Sébastien Simard
      The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying processes in the pharmaceutical industry. In this paper, drying of particles with a pilot-scale batch fluidized bed dryer (FBD) is studied using a in-line NIR probe. A consolidated phenomenological state-space model of an FBD based on mass and energy balances is calibrated applying a nonlinear least-square identification to experimental data (grey-box modeling). Then, relying on the calibrated model, a nonlinear model predictive controller and a moving horizon state estimator are designed. The objective is to reach a specific particle moisture content setpoint at the end of the drying batch while decreasing cycle time and limiting particle temperature. A penalty term on the energy consumption can also be added to the usual tracking control cost function. Compared to a typical FBD operation in industry (mostly open-loop), it is shown that the drying time and the energy consumption can be efficiently managed on the pilot-scale process while limiting various operation problems like under drying, over drying, or particles overheating.

      PubDate: 2017-05-08T08:10:17Z
  • Relaxed static stability based on tyre cornering stiffness estimation for
           all-wheel-drive electric vehicle
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Jun Ni, Jibin Hu, Changle Xiang
      A novel dynamics control approach for all-wheel-drive electric vehicle (EV), relaxed static stability (RSS) approach is proposed with two advantages. Firstly, it allows vehicle lateral dynamics system to be inherent unstable to improve configuration flexibility. Secondly, handling performance could be improved based on closed-looped pole assignment with additional yaw moment. In this paper, basic control framework of RSS is proposed, including ‘Desired Pole Location’, ‘Pole Assignment’ and ‘Tyre Cornering Stiffness Estimation’ modules. The tyre cornering stiffness is estimated online to improve the robustness of the controller. The experiments based on an EV testbed show the performance and efficiency of RSS.

      PubDate: 2017-05-08T08:10:17Z
  • Trajectory planning and tracking control for the temperature distribution
           in a deep drawing tool
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Timo Böhm, Thomas Meurer
      The deep drawing process and the resulting product quality essentially rely on the temperature distribution inside the tool. For temperature manipulation and control a flatness-based design technique for thermal trajectory planning and feedforward control for a deep drawing tool is developed based on a distributed parameter system description. Heating cartridges, that are embedded into the tool structure, serve as actuators to insert energy into the system with the desire to transfer the spatial-temporal temperature distribution from an initial to a desired final stationary profile. To address the complex-shaped geometry of the tool a high-order finite element (FE) approximation is deduced and combined with model-order reduction techniques to determine a sufficiently low order system representation that is applicable for optimal actuator placement. For this, a mixed-integer optimization problem is formulated based on a particular reduced-order formulation of the controllability Gramian. The resulting actuator configuration is exploited for flatness-based trajectory planning by constructing a virtual output that differentially parametrizes any system state and input. This implies a particularly intuitive approach to solve the thermal trajectory planning problem. Convergence of the differential parametrization is analyzed in the continuous limit as the finite element approximation approaches the continuum model. Re-summation techniques are integrated into the design to enhance the domain of applicability of the approach. The feedforward control is combined with industry-standardized proportional-integral-derivative (PID) output error feedback control within the so-called two-degree-of-freedom (2DOF) control concept. Simulation and experimental results obtained for a fully equipped forming tool are presented and confirm the applicability of the proposed design technique and the tracking performance. In addition, the results of this paper present a first experimental validation of flatness-based trajectory planning for thermal systems with three-dimensional spatial domain.

      PubDate: 2017-05-08T08:10:17Z
  • A novel approach to monitoring and maintenance of industrial PID
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Xinqing Gao, Chao Shang, Dexian Huang, Fan Yang
      Due to process nonlinearities and operating condition changes, industrial processes frequently encounter significant dynamics variations, which would compromise the long-term effectiveness of controller monitoring schemes and leads to superfluous alarms. To address these issues, a novel performance benchmark based on the min-max principle is developed for industrial PID controllers, which has satisfactory applicability for nonlinear processes with operating condition switches. Furthermore, a holistic workflow of monitoring and maintenance of industrial PID controllers is proposed, including online identification of process models, poor control detection based on the accessible benchmark, and maintenance guides for poorly behaved controllers. Both simulation and industrial cases studies are presented to demonstrate the effectiveness of the proposed method.

      PubDate: 2017-05-08T08:10:17Z
  • Position Control of an Over‐Actuated Direct Hydraulic Cylinder Drive
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Lasse Schmidt, Morten Groenkjaer, Henrik C. Pedersen, Torben O. Andersen
      This paper considers the analysis and control strategy for a novel direct hydraulic cylinder drive, that is over-actuated in the sense that it has more inputs than sensible outputs. Efforts to overcome the inherent loss of energy due to th+rottling in valve driven hydraulic drives are many, and various approaches have been proposed by research communities as well as the industry. Recently, a so-called Speed-variable Switched Differential Pump was proposed for direct drive of hydraulic differential cylinders. The main idea with this drive is to utilize an electric rotary drive with the shaft connected to three oppositely oriented fixed displacement gear pumps to actuate a differential cylinder. To ensure a high stiffness of the drive, this is constructed such that the transmission line pressures will increase for pump output flows exceeding pump leakages, and proportional valves provides the ability to bleed off flow from the transmission lines to achieve reasonable pressure levels. This design renders the drive over-actuated as the line pressures and the cylinder piston motion cannot be controlled independently, due to the pressure difference being motion generating. In order to achieve satisfactory performance of this drive, a state coupling analysis is presented along with a control strategy based on state decoupling synthesized from input-output transformations. This includes control schemes for the transformed system. The proposed control strategy is experimentally verified on a drive prototype, and results demonstrate that satisfactory overall performance-, and in particular highly accurate position tracking is achieved.

      PubDate: 2017-05-02T08:00:11Z
  • Shared control for lane departure prevention based on the safe envelope of
           steering wheel angle
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Dongkui Tan, Wuwei Chen, Hongbo Wang, Zhengang Gao
      The ability to prevent lane departure has become an important feature for commercialized vehicles. This paper proposes a shared steering assistance strategy based on a safe envelope of steering wheel angle (SWA). This solves the human-machine conflict issue in lane departure prevention (LDP) system which uses steering control to help the driver keep the vehicle within the correct lane. The system combines a driver steering control model, current vehicle states and vehicle-road deviation. The desired SWAs are calculated when the driver intends to drive along the left or right side of the lane, and then the two angles are used to generate the safe envelope. Next, a driver intention estimator is designed to predict driver’s intended SWA and the assistance control is activated by judging whether the driver intended SWA is go beyond the safe envelope. Finally, a H∞ controller and a disturbance observer are developed to determine the assistance torque. In this way, the SWA is limited to safe values to mitigate lane departure and the controller intervention is minimized. The effectiveness of the proposed method is evaluated via numerical simulation with different driving scenarios and human-in-the-loop experiment on a driving simulator. The obtained results show that this method not only can avoid lane departures effectively, but also ensures a good human-machine cooperative performance.

      PubDate: 2017-05-02T08:00:11Z
  • A robust adaptive fuzzy variable structure tracking control for the
           wheeled mobile robot: Simulation and experimental results
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Mauricio Begnini, Douglas Wildgrube Bertol, Nardênio Almeida Martins
      In this paper an adaptive fuzzy variable structure control (kinematic control) integrated with a proportional plus derivative control (dynamic control) is proposed as a robust solution to the trajectory tracking control problem for a differential wheeled mobile robot. The variable structure controller, based on the sliding mode theory, is a well known, proven control method, fit to deal with uncertainties and disturbances (e.g., structural and parameter uncertainties, external disturbances and operating limitations). To minimize the problems found in practical implementations of the classical variable structure controllers, an adaptive fuzzy logic controller replaces the discontinuous portion of the control signals (avoiding the chattering), causing the loss of invariance, but still ensuring the robustness to uncertainties and disturbances without having any a priori knowledge of their boundaries. Moreover, the adaptive fuzzy logic controller is a feasible tool to approximate any real continuous nonlinear system to arbitrary accuracy, and has a simple structure by using triangular membership functions, a low number of rules that must be evaluated, resulting in a lower computational load for execution, making it feasible for real time implementation. Stability analysis and the convergence of tracking errors as well as the adaptation laws are guaranteed with basis on the Lyapunov theory. Simulation and experimental results are explored to show the verification and validation of the proposed control strategy.

      PubDate: 2017-05-02T08:00:11Z
  • Hybrid electric vehicle fuel minimization by DC-DC converter
           dual-phase-shift control
    • Abstract: Publication date: July 2017
      Source:Control Engineering Practice, Volume 64
      Author(s): Simos A. Evangelou, M.A. Rehman-Shaikh
      The paper introduces an advanced DC-link variable voltage control methodology that improves significantly the fuel economy of series Hybrid Electric Vehicles (HEVs). The DC-link connects a rectifier, a Dual Active Bridge (DAB) DC-DC converter and an inverter, interfacing respectively the two sources and the load in a series HEV powertrain. The introduced Dual Phase Shift (DPS) proportional voltage conversion ratio control scheme is realized by manipulating the phase shifts of the gating signals in the DAB converter, to regulate the amount of DAB converter power flow in and out of the DC-link. Dynamic converter efficiency models are utilized to account for switching, conduction, copper and core losses. The control methodology is proposed on the basis of improving the individual efficiency of the DAB converter but with its parameters tuned to minimize the powertrain fuel consumption. Since DPS control has one additional degree of freedom as compared to Single Phase Shift (SPS) voltage control schemes, a Lagrange Multiplier optimization method is applied to minimize the leakage inductance peak current, the main cause for switching and conduction losses. The DPS control scheme is tested in simulations with a full HEV model and two associated conventional supervisory control algorithms, together with a tuned SPS proportional voltage conversion ratio control scheme, against a conventional PI control in which the DC-link voltage follows a constant reference. Nonlinear coupling difficulties associated with the integration of varying DC-link voltage in the powertrain are also exposed and addressed.

      PubDate: 2017-05-02T08:00:11Z
  • Optimal pressure sensor placement and assessment for leak location using a
           relaxed isolation index: Application to the Barcelona water network
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Miquel À. Cugueró-Escofet, Vicenç Puig, Joseba Quevedo
      Water distribution networks are large complex systems affected by leaks, which often entail high costs and may severely jeopardise the overall water distribution performance. Successful leak location is paramount in order to minimize the impact of these leaks when occurring. Sensor placement is a key issue in the leak location process, since the overall performance and success of this process highly depends on the choice of the sensors gathering data from the network. Common problems when isolating leaks in large scale highly gridded real water distribution networks include leak mislabelling and the obtention of large number of possible leak locations. This is due to similarity of leak effect in the measurements, which may be caused by topological issues and led to incomplete coverage of the whole network. The sensor placement strategy may minimize these undesired effects by setting the sensor placement optimisation problem with the appropriate assumptions (e.g. geographically cluster alike leak behaviors) and by taking into account real aspects of the practical application, such as the acceptable leak location distance. In this paper, a sensor placement methodology considering these aspects and a general sensor distribution assessment method for leak diagnosis in water distribution systems is presented and exemplified with a small illustrative case study. Finally, the proposed method is applied to two real District Metered Areas (DMAs) located within the Barcelona water distribution network.

      PubDate: 2017-04-04T03:21:57Z
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