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OPTIMAL SELF TUNING NEURAL NETWORK controlLER DESIGN

IFAC Proceedings Volumes 2005年第1期38卷 384-389页

作者： Ladislav Körösi Štefan Kozák Department of Automatic Control Systems Faculty of Electrical Engineering and Information Technology SUT Ilkovičova 3 812 19 Bratislava Slovak Republic

The proposed paper deals with modeling and control of continuous-time processes using artificial neural network with orthogonal activation functions, applicable for real-time control. A genetic algorithm has been used to find the optimal neural structure for on-line identification with the best learning algorithm. A moving prediction horizon in the control algorithm found by genetic algorithm has been compared with a constant prediction horizon. The proposed algorithms were verified on practical control problem and have proved a good performance.

关键词： neural-network models neural control optimal control on-line control genetic algorithms

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Predictive Fuzzy control Application

Predictive Fuzzy Control Application

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Eurocon

作者： J. Paulusova S. Kozak Department of Automatic Control Systems Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia

In this paper a robust predictive fuzzy control (PFC) methods for a nonlinear plant is addressed, proposed and tested. The paper consisting of theoretical and practical parts offers a new approach for intelligent fuzzy robust control design and its successful application. The structure of the fuzzy controller, online model identification and optimal performance index are analyzed, described and verified. The proposed PFC is demonstrated on two examples which one is applied to control of the concentration in the chemical reactor by manipulating its flow rate. The obtained simulation results show that the proposed algorithm is applicable for effective control of highly nonlinear processes that operate over a wide range of working space

关键词： Fuzzy control Predictive control Robust control Three-term control Fuzzy logic Performance analysis Chemical reactors electrical equipment industry Industrial control Process control

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Robust genetic algorithm approach to modelling and control

Robust genetic algorithm approach to modelling and control

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IEEE International Symposium on Intelligent Signal Processing

作者： S. Kozak R. Memersheimer A. Kozakova Department of Automatic Control Systems Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia

The paper deals with robust intelligent control of linear dynamical systems using algebraic polynomial theory in combination with the genetic algorithms (GA). It shows that the conventional robust polynomial synthesis approach can be successfully modified so as to improve performance by applying genetic algorithms for tuning controller parameters. A general algorithm has been developed for optimal polynomial controller tuning that enables to generate optimal and robust control actions for both SISO and MIMO systems. Moreover, the proposed methodology guarantees finding global optimum and enables achieving a higher performance compared with the conventional approaches. The proposed robust intelligent algorithm involving the intelligent searching procedure has been tested on a case study (control of a servo system with a changing momentum of inertia). Obtained results verify the possibility to improve the performance using combination of a polynomial algebraic controller and a genetic algorithm.

关键词： Robust control Genetic algorithms Polynomials control systems Intelligent control control system synthesis Optimal control MIMO System testing Servomechanisms

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Non-linear Predictive control for a Distillation Column

Non-linear Predictive Control for a Distillation Column

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IEEE Conference on Decision and control

作者： A. Rueda S. Cristea C. de Prada R. De Keyser Department of Systems Engineering and Automatic Control Faculty of Sciences c/Real de Burgos sln University of Valladolid Spain EeSA-Department of Electrical Energy Systems and Automation Ghent University Gent Belgium

ISBN: (纸本)0780395670

In this paper an alternative approach to non-linear predictive control is presented. It is based on iterative linearisation of the model response so that the same closed loop responses as in the pure non-linear approach are obtained but with reduced computation times and more efficient optimisation tools. The method is applied to a high purity distillation column and some results are presented showing the behaviour of the proposed algorithm.

关键词： Predictive control Distillation equipment Iterative methods Industrial control Constraint optimization Iterative algorithms electrical equipment industry Sampling methods Quadratic programming Pressure control

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HAND MOVEMENT IMPROVEMENT ON VISUAL TARGET TRACKING BY MODEL-BASED COMPENSATOR

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IFAC Proceedings Volumes 2005年第1期38卷 166-171页

作者： Takenao Sugi Junko Ide Masatoshi Nakamura Hiroshi Shibasaki Department of Electrical and Electronic Engineering Faculty of Science and Engineering Saga University Honjomachi Saga 840-8502 Japan Department of Literature Division of Social Welfare Seinan Gakuin University Fukuoka 814-8511 Japan Department of Advanced Systems Control Engineering Graduate School of Science and Engineering Saga University Saga 840-8502 Japan National Institute of Neurological Disorders and Stroke NIH Bethesda USA

Brain dysfunction in the cerebral cortex, cerebellum and/or basal ganglia causes serious movement disorders such as cerebellar ataxia, Parkinson disease and so on. Compensation of hand movement by adding an external force will recover the motor function and will be helpful for improving the quality of patients' daily life. This paper proposes a method for compensating human hand movement on visual target tracking by adding an assistant force. Mathematical model was obtained from the measurement data of visual target tracking for each subject, and the compensator was constructed based on the model. Effectiveness of the compensation method was investigated through the experiment.

关键词： Hand Movement Compensation Visual Target Tracking Modeling Assistant Force Model-Based Compensator Movement disorders

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Robust adaptive control of quasi-LPV systems

Robust adaptive control of quasi-LPV systems

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Xiukun Wei L. Del Re Jindong Tan Faculty of the institute of Design and Control of Machatronical Systems Johannes Kepler University Linz Austria Johannes Kepler Universitat Linz Linz AT Faculty of Department of Electrical and Computer Engineering Michigan Technological University USA

In this paper a robust adaptive pole placement method for a class of linear parameter varying (LPV) system based on input-output description is constructed after the LPV system model, including its un-modeled error model term, is presented. The recursive least square estimation algorithm with dead zone is applied for the parameter estimation. The robust stability of closed-loop system is analyzed and the robust bound is derived. One simulation example illustrates the effectiveness of the control algorithm and demonstrates that the adaptive control based on LPV model can achieve better performance than the controller based on linear time varying (LTV) model

关键词： Robust control Adaptive control Least squares approximation Robustness Parameter estimation Nonlinear systems control systems Programmable control State feedback Robust stability

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Mixed H2/H∞ and robust control of differential linear repetitive processes

Mixed H2/H∞ and robust control of differential linear repet...

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IEEE Conference on Decision and control

作者： W. Paszke K. Gakowski E. Rogers A. Kummert D.H. Owens Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland School of Electronics and Computer Science University of Southampton Southampton UK Faculty of Electrical University of Wuppertal Wuppertal Germany Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Repetitive processes are a distinct class of 2D systems (*** propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. Here we give new results on the design of physically based control laws and, in particular, the first results on a mixed H 2 /H ∞ approach and on H 2 control in the presence of uncertainty in the process model.

关键词： Robust control control systems Linear systems Uncertainty Writing Disk drives Process control Iterative algorithms control engineering computing Computer science

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The influence of feedback/feedforward control on relaxed pass profile controllability of discrete linear repetitive processes

The influence of feedback/feedforward control on relaxed pas...

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International Workshop on Multidimensional (nD) systems

作者： L. Hladowski K. Galkowski E. Rogers A. Kummert D.H. Owens Institute of Control and Computation Engineering University of Zielona Gora Zielona Gora Poland University of Wuppertal Germany School of Electronics and Computer Science University of Southampton Southampton UK Faculty of Electrical Information and Media Engineering Communication Theory University of Wuppertal Germany Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Repetitive processes are a distinct class of 2D systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. Here we give the first results on how feedback/feedforward control action can be used to influence one form of controllability for processes with discrete dynamics.

关键词： Linear feedback control systems controllability Integrated circuit modeling control engineering computing Vectors Communication system control Computer science systems engineering and theory State-space methods Multidimensional systems

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OPTIMIZATION OF POWER SYSTEM STABILIZER BY GENETIC ALGORITHM

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IFAC Proceedings Volumes 2005年第1期38卷 274-278页

作者： Ján MurgaŜ Ivan Sekaj Martin Foltin Eva Mikloviĉová Department of Automatic Control Systems Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkoviĉova 3 812 19 Bratislava Slovak Republic tel.: 02 602 91 781 fax.: 02 654 29 734

Power system stabilizers (PSS) play an important role in damping of power system oscillations. An intensive research activity has been devoted to design of their structure and optimal setting of their parameters. In this paper the simultaneous optimization of multiloop PSS and automatic voltage regulator parameters (AVR) by means of genetic algorithm is proposed. Using an example of the 259 MVA turbogenerator excitation system in the nuclear power plant Mochovce (Slovak Republic) it is shown that the genetic algorithms are able to find the optimal parameters of excitation system so that the requirements on terminal voltage performances as well as on damping of active power oscillations are satisfied.

关键词： power system stabilizers parameter optimization genetic algorithm power system simulation performance index

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REDUCING THE EFFECT OF UNMODELED DYNAMICS BY MRAC control LAW MODIFICATION

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IFAC Proceedings Volumes 2005年第1期38卷 271-275页

作者： Eva Miklovičová Ján Murgaš Michal Gonos Department of Automatic Control Systems Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovičova 3 812 19 Bratislava Slovak Republic tel.: 02 602 91 604 fax.: 02 654 29 734

Solving a tracking problem does not always give desired results even when the adaptive control methods are used. Some difficulties may occur when the apriori assumptions laid down for the problem solution are not satisfied. One of the serious issues is the existence of unmodeled dynamics in the tracking problem. The proposed solutions are mainly based on robustification of the adaptation law. In this paper we propose to reduce the effect of unmodeled dynamics using the MRAC control law modification so that the standard adaptation law ensures the sufficiently small tracking error.

关键词： model reference adaptive control Lyapunov methods tracking systems

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