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Modified hildreth’s method applied in multivariable model predictive control 3rd

3rd Conference on Innovation, Engineering and Entrepreneurship, Regional HELIX 2018

作者： Kubalcik, Marek Bobal, Vladimir Barot, Tomas Department of Process Control Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 05 Czech Republic Department of Mathematics with Didactics Faculty of Education University of Ostrava Mlynska 5 Ostrava701 03 Czech Republic

ISBN: (纸本)9783319913339

A significantly important part of model predictive control (MPC) with constraints are algorithms of numerical optimization. Reduction of the computational complexity of the optimization methods has been widely researched. The reason is that in certain cases of predictive control of fast dynamics processes an optimization algorithm may not be feasible within the sampling period time. This situation occurs particularly when requirements on control are more complex, e.g. in the multivariable control. Hildreth’s method based on the dual-problem-optimization-principles has been widely applied and implemented in model predictive control. However, modifications of this method are not widely described in context of model predictive control. This paper proposes a modification of Hildreth’s method, which reduces the computational complexity of the algorithm, and its application in the multivariable predictive control. © 2019, Springer International Publishing AG, part of Springer Nature.

关键词： Quadratic programming

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Statistical analysis of control quality of MPC using testing hypothesis

Statistical analysis of control quality of MPC using testing...

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23rd International Conference on Circuits, Systems, Communications and Computers, CSCC 2019

作者： Kubalcik, Marek Bobal, Vladimir Barot, Tomas Department of Process Control Tomas Bata University in Zlin Faculty of Applied Informatics Nad Stranemi 4511 Zlin76005 Czech Republic Department of Mathematics with Didactics University of Ostrava Faculty of Education Fr. Sramka 3 Ostrava70900 Czech Republic

Methods of the statistical induction have a significant role in the quantitative research. In a wide spectrum of research areas, the methods based on testing hypotheses have been frequently used. However, in the area of the process control, testing hypothesis has not been widely considered as an established tool for signal analyses, although signals in control loops are suitable for analysis by means of quantitative statistical methods due to their stochastic character. Particularly, a statistical paired comparison can be applied for analysis of control quality achieved with different control algorithms. This comparison can be based on a paired comparison of corresponding signals obtained with different or modified control algorithms. The aim of this paper is a proposal of incorporation of testing hypothesis to analysis of control quality. The analysis was performed on a strictly defined significance level 0.001, which is a standardly used value in technical applications. As an example was demonstrated analysis of control quality achieved with two versions of a predictive controller. Finally, achieved results of paired comparison using testing hypothesis are discussed. © 2019 The Authors, published by EDP Sciences.

关键词： Stochastic systems

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Reduction of the Optimization Efforts with Predictive control by Using Non-Equidistant Prediction Points

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IFAC Proceedings Volumes 2003年第8期36卷 57-62页

作者： U. Schmitz R. Haber R. Bars Department of Plant and Process Engineering Laboratory of Process Control University of Applied Science Cologne D-50619 Köln Betzdorf er Str. 2 Germany fax: +49-221-8275-2836 Department of Automation and Applied Informatics MTA-BME Control Research Group Budapest University of Technology and Economics Hungary

With predictive control most of the computation time is spent for the simulation of the predicted variables and for the optimization if constraints or nonlinear processes are assumed. In addition to the known blocking technique for the manipulated variable another possibility is calculating the control error not in each sampling point of the prediction horizon but only in some coincidence points. It will be shown that the best choice is to allocate the coincidence points exponentially thus that with small prediction steps more and with increasing prediction steps less coincidence points are considered. As a practical example the multivariable control of a distillation column model illustrates the benefits of the method presented.

关键词： Predictive control optimal control control applications chemical industry execution time

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Long-range optimal model and multi-step-ahead prediction identification for predictive control

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IFAC Proceedings Volumes 2003年第16期36卷 477-482页

作者： R. Haber U. Schmitz R. Bars Department of Plant and Process Engineering Laboratory of Process Control University of Applied Science Cologne D-50679 Köln Betzdorfer Str. 2 Germany fax: +49-221-8275-2836 Department of Automation and Applied Informatics Control Research Group of the Hungarian Academy of Sciences Budapest University of Technology and Economics Hungary

Long-range optimal prediction algorithms use the predicted output for several steps ahead. The prediction based on traditionally estimated model parameters does not result in an optimal prediction if the measurements are noisy or/and model structure differs from real process structure. In this paper two different identification schemes are presented and compared: long-range predictive single-model identification and simultaneous multi-step-ahead prediction identification. It is shown that the first method is easier to realize but the second one leads to more accurate results. Both methods are derived for a first-order model in details. Simulation runs and a level control example illustrate the algorithms presented.

关键词： process identification prediction parameter estimation predictive control

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ADAPTIVE DUAL control OF NONLINEAR LIQUID SYSTEM

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IFAC Proceedings Volumes 2007年第13期40卷 483-488页

作者： Vladimír Bobál Petr Chalupa Petr Dostál Tomas Bata University in Zlín Faculty of Applied Informatics Department of Process Control Nad Stránemi 4511 760 05 Zlín 5 Czech Republic

The general task of optimal adaptive control with recursive identification (self-tuning control) is very complicated problem. This problem is solved usually by the separation of identification and control – the Certainty Equivalency (CE) Principle. The aim of this paper is to present the solution of this problem using the Dual Adaptive control (Bicriterial Approach). The main idea of this approach involves two cost functions: (1) the system output should track cautiously the desired reference signal; (2) the control signal should excite the controlled process sufficiently for accelerating the parameter estimates. This approach was verified by a real-time control of nonlinear time varying laboratory model – DTS200 Three Tank System.

关键词： Self-tuning algorithms Dual control Autoregressive models Recursive least squares method Nonlinear systems Real-time systems

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Advanced process manipulation of magnesia sintering

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IFAC Proceedings Volumes 2008年第2期41卷 718-723页

作者： Imrich KOŠTIAL Ján SPIŠÁK Ján MIKULA Ján GLOČEK Pavol Nemčovský Ján TERPÁK Department of Applied Informatics and Process Control BERG Faculty Technical University of Košice B. Němcovej 3 042 00 Košice Slovak Republic

Manipulation process is connecting of our macroscopic world to the microscopic or nanoscopic one. Manipulation can occur in a variety of ways. Outside manipulation take control over the process by external forces. Inside process manipulation is becoming a part of the process. This process manipulation is called advanced process manipulation (APM). Possibility of process manipulation may substantially enhance the process effectiveness. In this paper methods of advanced process manipulation are presented. An incremental manipulation process will be defined as a sequence of basic operations. process manipulation generally requires custom-built system capable of performing of manipulation procedures. The progress in manipulation techniques can extend the application of the manipulated system. We have developed a simulation based system which was successfully implemented for designing of APM systems and control process in ways that are not conventionally possible. The developed system was applied on magnesia sintering process in shaft and rotary furnaces.

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Preferences and Decisions under Incomplete Knowledge 1

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丛书名： Studies in Fuzziness and Soft Computing

1000年

作者： János Fodor Bernard Baets Patrice Perny

ISBN: (数字)9783790818482

ISBN: (纸本)9783790813036;9783790824742

Nowadays, decision problems are pervaded with incomplete knowledge, i.e., imprecision and/or uncertain information, both in the problem description and in the preferential information. In this volume leading scientists in the field address various theoretical and practical aspects related to the handling of this incompleteness. The problems discussed are taken from multi-objective linear programming, rationality considerations in preference modelling, non-probabilistic utility theory, data fusion, group decision making and multicriteria decision aid. The book is oriented towards researchers, graduate and postgraduate students in decision analysis, fuzzy sets and fuzzy logic, and operations research/management science.

关键词： Operations Research/Decision Theory Artificial Intelligence Economic Theory/Quantitative Economics/Mathematical Methods IT in Business

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Nonlinear control of a shell and tube heat exchanger

Nonlinear control of a shell and tube heat exchanger

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28th European Conference on Modelling and Simulation, ECMS 2014

作者： Dostál, Petr Bobál, Vladimír Vojtěšek, Jiâí Centre of Polymer Systems University Institute Tomas Bata University in Zlin Nad Ovcirnou 3685 760 01 Zlin Czech Republic Department of Process Control Faculty of Applied Informatics Tomas Bata University in Zlin Nad Stranemi 4511 760 05 Zlin Czech Republic

ISBN: (纸本)9780956494481

The paper deals with design and simulation of nonlinear adaptive control of a shell and tube heat exchanger. The method is based on factorization of the controller on a nonlinear static part and an adaptive linear dynamic part. The nonlinear static part is derived using inversion and subsequent exponential approximation of simulated or measured steady-state characteristics of the exchanger. The linear dynamic part is then obtained from an external linear model of nonlinear elements of the closed-loop. The parameters of the external linear model are recursively estimated via a corresponding delta model. The control law in the 1DOF and 2DOF control system structures is derived using the polynomial approach. Proceedings 28th European Conference on Modelling and Simulation © ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors).

关键词： Parameter estimation

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Simulation of cascade control of a continuous stirred tank reactor 29

Simulation of cascade control of a continuous stirred tank r...

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29th European Conference on Modelling and Simulation, ECMS 2015

作者： Dostál, Petr Bobál, Vladimir Vojtěšek, Jiří Centre of Polymer Systems University Institute Tomas Bata University in Zlin Nad Ovcirnou 3685 Zlin760 01 Czech Republic Department of Process Control Faculty of Applied Informatics Tomas Bata University in Zlin Nad Stranemi 4511 Zlin760 05 Czech Republic

ISBN: (纸本)9780993244001

The paper presents simulation results of the cascade control of a continuous stirred tank reactor. The control is performed in primary and secondary control-loops where the primary controlled output of the reactor is the concentration of a desired reaction product, and, the secondary output is the reactant temperature. A common control input is the coolant flow rate. The controller in the primary control-loop is a P-controller with the gain calculated using simulated or measured steady-state characteristics of the reactor. The controller in the secondary control-loop is an adaptive controller. The proposed method is verified by control simulations. © ECMS Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors).

关键词： controllers

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Application of Kronecker summation method in computation of robustly stabilizing PI controllers for interval plants

Application of Kronecker summation method in computation of ...

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作者： Matušů, Radek Prokop, Roman Matejičková, Katarína Bakošová, Monika Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 76005 Zlín Czech Republic Department of Information Engineering and Process Control Faculty of Chemical and Food Technology Slovak University of Technology in Bratislava Radlinského 9 81237 Bratislava Slovakia

ISBN: (纸本)9789604741991

The contribution deals with design of continuous-time robustly stabilizing PI controllers for interval systems using the combination of Kronecker summation method, sixteen plant theorem and an algebraic approach to controller tuning. The effectiveness and practical applicability of the proposed method is demonstrated in control of a 3rd order nonlinear electronic plant.

关键词： Continuous time systems

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