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ENGINEERING (1203 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     Full-text available via subscription   (Followers: 5)
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Abstract and Applied Analysis     Open Access   (Followers: 3)
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ACS Nano     Full-text available via subscription   (Followers: 222)
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Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
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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)
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Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
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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)
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Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
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Asian Journal of Biotechnology     Open Access   (Followers: 8)
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at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
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Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
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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: 3)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
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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)
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Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
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Biotechnology Progress     Hybrid Journal   (Followers: 39)
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Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
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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: 7)
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: 5)
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: 9)
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: 4)
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)
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Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 25)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 256)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 181)
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Composites Science and Technology     Hybrid Journal   (Followers: 169)
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Control Engineering Practice     Hybrid Journal   (Followers: 41)
Control Theory and Informatics     Open Access   (Followers: 7)
Corrosion Science     Hybrid Journal   (Followers: 25)
CT&F Ciencia, Tecnologia y Futuro     Open Access  

        1 2 3 4 5 6 7 | Last

Journal Cover Control Engineering Practice
  [SJR: 1.354]   [H-I: 84]   [41 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0967-0661
   Published by Elsevier Homepage  [3034 journals]
  • 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
  • Contents list
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63

      PubDate: 2017-05-02T08:00:11Z
  • Longitudinal tunnel ventilation control. Part 1: Modelling and dynamic
           feedforward control
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Nikolaus Euler-Rolle, Martin Fuhrmann, Markus Reinwald, Stefan Jakubek
      Road tunnels exceeding a certain minimum length are equipped with a ventilation system. In case of a fire it is used to achieve a predefined air flow velocity in the tunnel by adequately controlling the installed jet fans in order to ensure sufficient visibility for persons to safely follow the escape routes. As the dynamics of the air flow in road tunnels strongly depend on the tunnel length, short tunnels with longitudinal ventilation systems pose a challenging control task. In this paper, non-linear dynamic feedforward control is proposed for longitudinal ventilation control in case of an emergency. For this purpose, an analytical non-linear zero-dimensional model of the air flow is feedback linearised. Due to its special properties, which are presented and analysed, two different versions of feedforward control are proposed: One is focused on performance, the other on robustness. Finally, the beneficial behaviour of the presented two-degrees-of-freedom control approach is demonstrated by its application to an Austrian motorway tunnel.

      PubDate: 2017-04-25T12:38:21Z
  • Control-oriented tools for the design and validation of the JT-60SA
           magnetic control system
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): N. Cruz, G. De Tommasi, M. Mattei, A. Mele, Y. Miyata, A. Pironti, T. Suzuki
      The construction and operation of the JT-60SA tokamak is the main project currently carried out jointly by Japan and the European Union under the Broader Approach agreement. Within the Integrated Project Team, Japanese and European scientists are developing and testing a number of tools to support preliminary studies and future operations of JT-60SA. Within this collaborative framework, European scientists are using a set of assessed modeling tools to design and validate possible solutions for the plasma magnetic control system of JT-60SA. This paper introduces these tools and describes a possible control architecture to be used on the JT-60SA tokamak. The effectiveness of the proposed architecture is shown by means of numerical simulations.
      Graphical abstract image Highlights

      PubDate: 2017-04-25T12:38:21Z
  • Ensemble-based simultaneous input and state estimation for nonlinear
           dynamic systems with application to wildfire data assimilation
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Huazhen Fang, Thayjes Srivas, Raymond A. de Callafon, Mulugeta A. Haile
      This paper presents a study of simultaneous input and state estimation for nonlinear dynamic systems, which is formulated as a filtering problem and defining the simultaneous input and state filtering (SISF) approach. The problem considers both unknown input and state variables, where the inputs offer a general description of unknown signals driving or existing in a system. To deal with the problem, a set of ensemble-based approaches for both filtering and smoothing are developed in a Bayesian statistical framework. The fundamental notion is to approximately represent the probability distributions of the unknown input and state variables conditioned on output measurements by ensembles of samples, propagate the ensembles to track the evolution of the probability distributions, and then extract the input and state estimates from the ensembles. The computational efficiency of the proposed method allows application characterized by high-dimensional nonlinear dynamic state representations. The results can be regarded as an extension of the celebrated ensemble Kalman filter (EnKF), which is intended for only state estimation by design, to the new inquiry on SISF. The proposed SISF approach is validated on the forty-dimension Lorenz'96 model. Furthermore, an elaborate demonstration of the effectiveness is illustrated on data-driven wildfire data assimilation, where uncertain wind conditions that act as an input driving the wildfire are estimated using SISF.

      PubDate: 2017-04-25T12:38:21Z
  • Contents list
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62

      PubDate: 2017-04-25T12:38:21Z
  • Longitudinal tunnel ventilation control. Part 2: Non-linear observation
           and disturbance rejection
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Martin Fuhrmann, Nikolaus Euler-Rolle, Michaela Killian, Markus Reinwald, Stefan Jakubek
      Tunnel ventilation control plays a key role in tunnel fire safety, nevertheless there is considerable scope for improving conventional control schemes. This paper proposes a practical approach on how to improve the disturbance attenuation ability of longitudinal tunnel ventilation systems by adding a non-linear unknown disturbance observer to an existing two-degrees-of-freedom control scheme in order to establish active disturbance rejection. The focus of attention is on tunnels using jet fans for fresh air supply. Conventional control does not specifically take into account external disturbances that tunnels are exposed to due to the momentum introduced by moving vehicles and meteorological circumstances like wind load onto the portals, or meteorological pressure differences between the portals. The proposed control scheme provides promising simulation as well as experimental results of a real tunnel implementation. The observer and rejection scheme's convergence and stability is analysed based on Lyapunov theory.

      PubDate: 2017-04-18T08:56:58Z
  • Prioritised objectives for model predictive control of building heating
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Edward O'Dwyer, Luciano De Tommasi, Konstantinos Kouramas, Marcin Cychowski, Gordon Lightbody
      Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have been widely reported. A key requirement for successful realisation of such approaches is that strategies are formulated in such a way as to be easily adapted to fit a wide range of buildings with little commissioning effort. This paper introduces an MPC-based building heating strategy, whereby the (typically competing) objectives of energy and thermal comfort are optimised in a prioritised manner. The need for balancing weights in an objective function is eliminated, simplifying the design of the strategy. The problem is further divided into supply and demand problems, separating a high order linear optimisation from a low order nonlinear optimisation. The performance of the formulation is demonstrated in a simulation platform, which is trained to replicate the thermal dynamics of a real building using data taken from the building.

      PubDate: 2017-04-18T08:56:58Z
  • Optimization control of a pulverizing system on the basis of the
           estimation of the outlet coal powder flow of a coal mill
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Yaokui Gao, Deliang Zeng, Jizhen Liu, Yifan Jian
      This study aimed to master the operating characteristics of a pulverizing system, improve the output control precision of the system, and reduce the fluctuation amplitude of the main operating parameters of coal-fired units. A nonlinear dynamic model of a direct-fired pulverizing system that considers the effect of coal moisture on the energy balance of a coal mill was established. Then, an estimated signal of the outlet coal powder flow of the coal mill was constructed as a new output control target of the pulverizing system. Finally, an output control optimization method for the pulverizing system was designed on the basis of this signal. Simulation results showed that the model effectively reflects the dynamic characteristics of a pulverizing system. In addition, the results of simulation were concordant with those of online measurements. The control scheme reduced the internal disturbances in the coal feed rate, thereby improving the tracking capability and control precision of the pulverizing system's output and enhancing the disturbance suppression capability of the mill outlet temperature. Thus, the designed control scheme can ensure the safe and stable operation of coal-fired units.

      PubDate: 2017-04-18T08:56:58Z
  • Entry guidance with smooth drag planning and non-linear tracking
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): R. Gifty, U.P. Rajeev, V.R. Lalithambika, M.V. Dhekane
      A guidance strategy is developed for the entry phase, meeting range requirements while honouring the constraints on heat flux, dynamic pressure and structural load on the vehicle. Space shuttle guidance is taken as the baseline and an improved strategy to plan and track a reference drag acceleration profile is developed. Trajectory planning is done in drag-energy plane. Drag acceleration and its derivatives are stored as function of specific energy. An analytical, continuous drag modulation strategy is developed for generating the reference trajectory on-board honouring the constraints. The modulated reference trajectory is tracked by a non-linear controller using Incremental Non-linear Dynamic Inversion technique (INDI). The guidance scheme is demonstrated in a short-range re-entry technology demonstrator vehicle. Simulation studies are carried out to establish the robustness of the guidance algorithm for a wide range of performance dispersions.

      PubDate: 2017-04-11T08:36:38Z
  • Sliding-based image-guided 3D needle steering in soft tissue
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Bita Fallahi, Carlos Rossa, Ron S. Sloboda, Nawaid Usmani, Mahdi Tavakoli
      This paper presents a sliding-based method for steering beveled-tip needles in a 3D environment. The controller determines the needle roll angle using the needle tip position deviation, obtained from ultrasound images, and its first time derivative. The stability of the closed-loop system is analyzed using 3D unicycle model for the needle, as a result of which parameter constraints are derived. In this method the needle is steered by performing adjustments of needle orientation, which reduces the tissue trauma and injury. The performance of this method is verified by performing experiments using phantom tissue for environments with and without obstacles.

      PubDate: 2017-04-11T08:36:38Z
  • 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
  • Identification of a multivariable nonlinear and time-varying mist reactor
    • Abstract: Publication date: June 2017
      Source:Control Engineering Practice, Volume 63
      Author(s): Chin Leei Cham, Ai Hui Tan, Wooi Haw Tan
      This paper considers the identification of a multivariable nonlinear and time-varying mist reactor system which presents an important system in the industry for applications in cell culture. A systematic approach is formulated for characterizing the linear dynamics, nonlinear distortion, disturbing noise and time variation. The best time-invariant approximation is introduced as part of the methodology in the proposed approach. By incorporating significant nonlinear terms into the model, the main source of disturbance can be determined with greater confidence. The power at the different harmonics is further capitalized upon in deriving an indicator for the relative variance of the time-varying delay.
      Graphical abstract image

      PubDate: 2017-04-04T03:21:57Z
  • Time-delay identification in dynamic processes with disturbance via
           correlation analysis
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Li-Juan Li, Ting-Ting Dong, Shu Zhang, Xiao-Xiao Zhang, Shi-Ping Yang
      A time-delay identification algorithm in closed-loop dynamic processes with disturbance based on maximum correlation analysis was proposed in this paper. To denoise the output data, the response of process disturbance was first estimated on routine data and then eliminated from the output. Next the incremental denoising process data were proposed to be used against the influence of system dynamic on the time-delay estimation. The correlations between the incremental input and different delayed output were computed and the delayed time corresponding to the maximum correlation was identified as the time-delay. The application in the Wood-Berry process and an industrial process showed the validity of the proposed algorithm.

      PubDate: 2017-04-04T03:21:57Z
  • Improved Stewart platform state estimation using inertial and actuator
           position measurements
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): I. Miletović, D.M. Pool, O. Stroosma, M.M. van Paassen, Q.P. Chu
      Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar to that experienced in actual flight. Accurate measurements of Stewart platform kinematic states are crucial for the application of advanced motion control algorithms and are highly valued in quantitative assessments of simulator motion fidelity. In the current work, a novel method for the reconstruction of the kinematic state of a Stewart platform is proposed. This method relies on an Unscented Kalman Filter (UKF) for a tight coupling of on-platform inertial sensors with measurements of the six actuator positions. The proposed algorithm is shown to be superior to conventional iterative methods in two main areas. First, more accurate estimates of motion platform velocity are obtained and, second, the algorithm is robust to inherent measurement uncertainties like noise and bias. The results were validated on the SIMONA Research Simulator (SRS) at TU Delft. To this end, an efficient implementation of the algorithm was driven, in real time, by actual sensor measurements from two representative motion profiles.

      PubDate: 2017-04-04T03:21:57Z
  • Issues in closed-loop needle steering
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Carlos Rossa, Mahdi Tavakoli
      Percutaneous needle insertion is amongst the most prevalent clinical procedures. The effectiveness of needle-base interventions heavily relies on needle targeting accuracy. However, the needle interacts with the surrounding tissue during insertion and deflects away from its intended trajectory. To overcome this problem, a significant research effort has been made towards developing robotic systems to automatically steer bevel-tipped needles percutaneously, which is a comprehensive and challenging control problem. A flexible needle inserted in soft tissue is an under-actuated system with nonholonomic constraints. Closed-loop feedback control of needle in tissue is challenging due to measurement errors, unmodelled dynamics created by tissue heterogeneity, and motion of targets within the tissue. In this paper, we review recent progress made in each of the complementary components that constitute a closed-loop needle steering system, including modelling needle-tissue interaction, sensing needle deflection, controlling needle trajectory, and hardware implementation.

      PubDate: 2017-03-28T03:07:06Z
  • The consistency control of mold level in casting process
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Ping Shen, Han-Xiong Li
      A new multiple periodic disturbance rejection control for casting process is proposed in this paper. Firstly, a high-precision multiple periodic disturbance detection method is designed. The accurate frequencies of the disturbance can be obtained. By using the disturbance observer and a group of filters with additional delay items, multiple periodic disturbance can be suppressed under time-delay environment. Then systematic control design is achieved based on the robust stability analysis. Finally, the efficiency of the proposed method is shown by comparisons between different methods and time-varying disturbance rejection in the consistency control of mold level.

      PubDate: 2017-03-28T03:07:06Z
  • EMD-based online Filtering of Process Data
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Xi Ma, Jinqiu Hu, Laibin Zhang
      In chemical industries, measurements corrupted by noise or outliers may affect operators’ recognition of the current situation and lead them to make inappropriate control decisions. Data quality is a critical factor for process monitoring and fault diagnosis. A robust online filtering method (OLREMD 1 1 OLREMD: robust EMD-based online filtering of process data. ) is proposed to implement online process data rectification with Empirical Mode Decomposition (EMD) as the basic algorithm. Tests with synthetic data show that OLREMD performs robustly with a lower sensitivity to parameters and improved performance on elimination of both noise and outliers. When applied to an industrial de-ethanizing column, OLREMD is shown to enhance the process monitoring performance.
      Graphical abstract image

      PubDate: 2017-03-28T03:07:06Z
  • Iterative Learning Control of Iteration-Varying Systems via Robust Update
           Laws with Experimental Implementation
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Berk Altın, Jeroen Willems, Tom Oomen, Kira Barton
      Iterative learning control (ILC) is an efficient way of improving the tracking performance of repetitive systems. While ILC can offer significant improvement to the transient response of complex dynamical systems, the fundamental assumption of iteration invariance of the process limits potential applications. Utilizing abstract Banach spaces as our problem setting, we develop a general approach that is applicable to the various frameworks encountered in ILC. Our main result is that robust invariant update laws lead to stable behavior in ILC systems, where iteration-varying systems converge to bounded neighborhoods of their nominal counterparts when uncertainties are bounded. Furthermore, if the uncertainties are convergent along the iteration axis, convergence to the nominal case can be guaranteed.

      PubDate: 2017-03-21T06:54:31Z
  • Fault prognosis of filamentous sludge bulking using an enhanced
           multi-output gaussian processes regression
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Yiqi Liu, Yongping Pan, Daoping Huang, Qilin Wang
      The activated sludge process (ASP) is widely adopted to remove pollutants in wastewater treatment plants (WWTPs). However, the occurrence of filamentous sludge bulking often compromises the stable operation of the ASP. For timely diagnosis of filamentous sludge bulking for an activated sludge process in advance, this study proposed a Multi-Output Gaussian Processes Regression (MGPR) model for multi-step prediction and presented the Vector auto-regression (VAR) to learn the MGPR modelling deviation. The resulting models and associated uncertainty levels are used to monitor the filamentous sludge bulking related parameter, sludge volume index (SVI), such that the evolution of SVI can be predicted for both one-step and multi-step ahead. This methodology was validated with SVI data collected from one full-scale WWTP. Online diagnosis and prognosis of filamentous bulking sludge with real-time SVI prediction were tested through a simulation study. The results demonstrated that the proposed methodology was capable of predicting future SVI with good accuracy, thereby providing sufficient time for filamentous sludge bulking.

      PubDate: 2017-03-21T06:54:31Z
  • Two-stage voltage control of subtransmission networks with high
           penetration of wind power
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Zhiyuan Tang, David J. Hill, Tao Liu
      Voltage issues are the main factors that limit the penetration level of wind power in subtransmission systems. In this paper, based on different control characteristics, we propose a two-stage coordinated control framework to deal with the negative voltage impacts caused by wind power fluctuations. In the first control stage, on-load tap changers (OLTCs) are used to deal with the voltage variations caused by large wind power fluctuations. In the second control stage, virtual power plants (VPPs) in the subtransmission network are used to handle the remaining slight voltage variations by controlling their reactive power. The second control stage only takes actions to support voltage regulations when control actions of the first control stage cannot meet the control requirements. Control actions of OLTCs and VPPs are obtained through multi-objective optimization based model predictive control and a fully distributed optimal dispatch scheme, respectively. The effectiveness of the proposed control method is tested through case studies based on the IEEE 14-bus test system and IEEE 30-bus test system with wind farms. In addition, through comparison with the traditional control method, our control scheme can reduce the control costs significantly and achieve the control targets at the same time.

      PubDate: 2017-03-16T10:42:58Z
  • Incipient fault detection with smoothing techniques in statistical process
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Hongquan Ji, Xiao He, Jun Shang, Donghua Zhou
      In modern industry, detecting incipient faults timely is of vital importance to prevent serious system performance deterioration and ensure optimal process operation. Recently, multivariate statistical process monitoring (MSPM) techniques have been extensively studied and widely applied to modern industrial systems. However, conventional fault detection indices utilized in statistical process monitoring are not sensitive to incipient faults with small magnitude. In this paper, by introducing two representative smoothing techniques, novel incipient fault detection strategies based on a generic fault detection index in MSPM are proposed. Fault detectability for each proposed strategy is analyzed. In addition, the effects of the smoothing parameters on fault detection, including advantages and disadvantages, are also investigated. Finally, case studies on a numerical example and two practical industrial processes are carried out to demonstrate the effectiveness of the proposed incipient fault detection strategies.

      PubDate: 2017-03-16T10:42:58Z
  • Proportional electro-hydraulic valves: An Embedded Model Control solution
    • Abstract: Publication date: May 2017
      Source:Control Engineering Practice, Volume 62
      Author(s): Wilber Acuña-Bravo, Enrico Canuto, Marco Agostani, Marco Bonadei
      Hierarchical control architectures are a common approach when hydraulic systems are under study; provided their multi-domain nature, the control scheme is commonly split into different hierarchical levels each one associated with a particular physical domain. This paper presents the application of a model-based control structure called Embedded Model Control (EMC) when a hierarchical scheme is implemented on an electro-hydraulic proportional valve. The overall control consists of two hierarchical loops: the inner loop is the solenoid current regulator with a closed loop bandwidth close to 1kHz. The outer loop is a position tracking control, in charge of the accurate positioning of the spool with respect to valve openings. The paper addresses the outer loop, i.e., the tracking of mechanical spool position by using the EMC. Analysis and synthesis are presented as well as experimental results obtained from a test rig provided by an industrial manufacturer.

      PubDate: 2017-03-16T10:42:58Z
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