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作者： Syafiie, S. Tadeo, F. Martinez, E. Department of Systems Engineering and Automatic Control Science Faculty University of Valladolid Prado de La Magdalena s/n 47011 Valladolid Spain Consejo Nacional de Investigaciones Científicas y Técnicas Avellaneda 3657 3000 Santa Fe Argentina

ISBN: (纸本)008045108X

This article presents a solution to pH control based on model-free intelligent control (MFIC) using reinforcement learning. This control technique is proposed because the algorithm gives a general solution for acid-base system, yet simple enough for its implementation in existing control hardware. in standard reinforcement learning, the interaction between an agent and the environment is based on a fixed time scale: during learning, the agent can select several primitive actions depending on the system state. A novel solution is presented, using multistep actions (MSA): actions on multiple time scales consist of several identical primitive actions. This solves the problem of determining a suitable fixed time scale to select control actions so as to trade off accuracy in control against learning complexity. The application of multi-step actions on a simulated pH process shows that the proposed MFIC learns to control adequately the neutralization process. Copyright © 2005 IFAC.

关键词： Process control

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Hierarchical model predictive control of integrated quality and quantity in drinking water distribution systems

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Urban Water Journal 2005年第2期2卷 125-137页

作者： Duzinkiewicz, K. Brdys, M. A. Chang, T. Department of Control Engineering Faculty of Electrical Engineering and Automatic Control Gdánsk University of Technology. G. Narutowicza 11/12 Gdánsk 80-952 Poland Department of Electronic Electrical and Computer Engineering School of Engineering The University of Birmingham Birmingham B15 2TT UK

An integrated approach to control of quantity and quality in water supply and distribution systems is proposed. The integrated control consists in optimising the operational cost, meeting a demand on water of desired quality and maintaining the system constraints. This constrained optimising control problem is complex due to nonlinearities, large dimension, output constraints, mixed-integer structure of the variables involved, at least two time scales in the system dynamics and an uncertainty. A sub-optimal two-level hierarchical control structure is proposed that allows incorporating the desired controller functions and yet making the synthesis of these functions possible. The algorithms for implementing the functionalities are proposed and discussed. Detail design of the lower level controller is presented and investigated. The controller performance is validated by simulation. [ABSTRACT FROM AUTHOR]

关键词： Bounding method Chlorine residuals Constraints Predictive control Transport delay Uncertain dynamic systems Water quality control

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PREDICTIVE control OF A PROCESS WITH VARIABLE DEAD-TIME

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IFAC Proceedings Volumes 2005年第1期38卷 309-314页

作者： Smaranda Cristea César de Prada Robin de Keyser Department of Systems Engineering and Automatic Control Faculty of Sciences c/ Real de Burgos s/n University of Valladolid Spain fax: +34 983 423161 tel: +34 983 423164 Department of Control Engineering & Automation University of Ghent Technologiepark-Zwijnaarde 9 B-9052 GHENT Belgium

This paper deals with the control of variable-delay processes, where the delay depends on the value of the manipulated variable, which results in a non-linear system difficult to control. As a reference process, the case of a heated tank where the controlled variable is the liquid temperature and the placement of the sensor introduce a transport delay in the control loop, has been considered. This challenging problem is approached from the perspective of predictive control, using the non-linear EPSAC controller.

关键词： Variable dead-time Predictive control Nonlinear control Delay systems

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NEURO-FUZZY control OF A PH PLANT

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IFAC Proceedings Volumes 2005年第1期38卷 195-200页

作者： M.J. Fuente G.I. Sainz M. Alonso A. Aguado Department of Systems Engineering and Control. Faculty of Science University of Valladolid. Prado de la Magdalena s/n 47011 Valladolid Spain ETSII. University of Valladolid. Paseo del Cauce s/n 47011 Valladolid Spain Department of Automatic Control ICIMAF Cuba

This paper studies the control of a pH process by using a neuro fuzzy controller with gain scheduling. As the process to be controlled is highly non-linear the PI-type fuzzy controller that will be used generally is not able to control the system adequately. For this, a very simple feedforward neural network trained on-line, is put at the output of the PI-type fuzzy controller in order to calculate the gain of the controller. This neuro-fuzzy regulator has been tested in real-time on a bench plant. On-line results show that the designed control system allows the plant to operate in a range of pH values, despite perturbations and variations of the plant parameters, obtaining good performance at the desired workings points.

关键词： Fuzzy controller neural networks Nonlinear process control real pH plant gain scheduling

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IMPROVEMENT OF FAULT DETECTION METHOD FOR NONLINEAR BLACK-BOX systemS BASED ON MULTI-FORM QUASI-ARMAX MODELING

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IFAC Proceedings Volumes 2005年第1期38卷 101-106页

作者： K. Kumamaru K. Inoue F. Tsubouchi T. Söderström Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka 820-8502 Fukuoka Japan Department of Automatic Control and Systems Analysis Institute of Technology Uppsala University P.O.Box 27 Uppsala Sweden

This paper is concerned with improvement of the KDI-based fault detection method so far developed by authors for nonlinear black-box systems. When modeling the system, Quasi-ARMAX model with multi-model structure is used. A fault due to unexpected change in system parameters will appear as the change of identified model. Kullback discrimination Information (KDI) can then be used as the fault detection index to evaluate the distortion in identified model. Several schemes to improve the fault detection performance are proposed, as well as the realization of a kind of fault isolation function based on a recognition approach in the model parameter space. The effectiveness of the method is verified through simulation studies on the ship propulsion system constructed for benchmark test.

关键词： Fault detection Kullback discrimination information non-linear system parameter estimation quasi-ARMAX model ship propulsion system

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INVESTIGATION OF PARAMETER PERTURBATION REGION FOR POSITIVE POLYNOMIALS

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IFAC Proceedings Volumes 2005年第1期38卷 469-474页

作者： Bernd Tibken Kamil Fatih Dilaver Department of Automatic Control Faculty of Electrical Information and Media Engineering University of Wuppertal Rainer-Gruenter-Str. 21 42119 Wuppertal Germany Tel : (+49) 0 202 439 19 52 Fax : (+49) 0 202 439 19 53

In this paper the robust positivity of polynomials under coefficient perturbation is investigated. This robust positivity of polynomials can be used for polynomial systems in order to determine the robust asymptotic stability of the system. It is assumed that the polynomials under investigation depend linearly on some parameters. The aim in the article is to determine the parameter perturbation region as a hypersphere, for which the polynomial is globally positive. The theorem of Ehlich and Zeller is used to achieve this aim. This theorem enables to give conditions in the parameter space for global positivity. These conditions are linear inequalities. By means of these inequalities an inner and an outer approximation are calculated to the relevant perturbation region which is a hypersphere. Two nontrivial examples conclude the paper and show the effectiveness of the presented method.

关键词： Linear Inequalities Nonlinear systems Optimization Polynomials Robustness Stability

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MODEL-FREE INTELLIGENT control USING REINFORCEMENT LEARNING AND TEMPORAL ABSTRACTION-APPLIED TO pH control

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IFAC Proceedings Volumes 2005年第1期38卷 127-132页

作者： S. Syafiie F. Tadeo E. Martinez Department of Systems Engineering and Automatic Control Science Faculty University of Valladolid Prado de la Magdalena s/n. 47011 Valladolid. Spain Consejo Nacional de Investigaciones Científicas Técnicas Avellaneda 3657 3000 Santa Fe Argentina

This article presents a solution to pH control based on model-free intelligent control (MFIC) using reinforcement learning. This control technique is proposed because the algorithm gives a general solution for acid-base system, yet simple enough for its implementation in existing control hardware. In standard reinforcement learning, the interaction between an agent and the environment is based on a fixed time scale: during learning, the agent can select several primitive actions depending on the system state. A novel solution is presented, using multi-step actions (MSA): actions on multiple time scales consist of several identical primitive actions. This solves the problem of determining a suitable fixed time scale to select control actions so as to trade off accuracy in control against learning complexity. The application of multi-step actions on a simulated pH process shows that the proposed MFIC learns to control adequately the neutralization process.

关键词： learning control intelligent control online learning agents process control neutralization process pH control temporal abstraction model free

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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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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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Doubly-fed induction machine as generator in wind power plant: nonlinear control algorithms with direct decoupling

Doubly-fed induction machine as generator in wind power plan...

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European Conference on Power Electronics and Applications

作者： N.P. Quang A. Dittrich P.N. Lan Faculty of Electrical Engineering Department of Automatic Control Key Lab of Automation Hanoi University of Technology Hanoi Vietnam Enerdrive Zurich Switzerland Fakultät Elektrotechnik und Informationstechnik Elektrotechnisches Institut Dresden University of Technology Dresden Germany

Currently the doubly fed induction machine (DFIM) is often used in wind power plants. The digital rotor current controller is always based on DFIM models linearized within a sampling period which does not correspond to the nonlinear nature of the DFIM. The paper deals with a nonlinear control scheme with direct decoupling and presents some first investigation results. This new controller helps to improve ride-through of the wind turbine during grid faults

关键词： Induction machines Induction generators Power generation Wind energy generation Wind energy Rotors Digital control Sampling methods Power system stability Wind turbines

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