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2003 IFAC Workshop on New Technologies for automation of the Metallurgical Industry 2003

作者： Jämsä-Jounela, S.-L. Vermasvuori, M. Kämpe, J. Kesti, A. Koskela, Kari Helsinki University of Technology Department of Chemical Technology Laboratory of Process Control and Automation Kemistintie 1 EspooFIN-02150 Finland Larox Corporation P.O. Box 29 Lappeenranta53101 Finland

Artificial intelligence methods such as expert systems, fuzzy systems, neural networks and combinations of these, have become invaluable tools in helping operators to monitor and control processes. These methods can also be used to run processes in a more economically effective way and, in the case of equipment malfunction, they can propose appropriate corrective measures. In this paper an operator support system for the Larox pressure filter is presented. Copyright © 2003 IFAC

关键词： Fault detection

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Nonlinear process identification and predictive control by the weighted sum of multi-model outputs 2

Nonlinear process identification and predictive control by t...

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2nd IFAC Conference on control Systems Design, CSD 2003

作者： Schmitz, U. Haber, R. Bars, R. Department of Plant and Process Engineering Laboratory of Process Control University of Applied Science Cologne Betzdorfer Str. 2 KolnD-50679 Germany Department of Automation and Applied Lnformatics Budapest University of Technology and Economics Goldmann Gyter 3 BudapestH-1111 Hungary

Most industrial processes are nonlinear. In such a case only a nonlinear model valid for the whole working area can ensure a good controller design. The nonlinear process is approximated by a multi-model consisting of the intelligent combination of some linear sub-models. As a very practical way the following identification strategy was used: Independent model parameter estimation in the different working points and the calculation of the global valid model output as the weighted sum of the sub-models. As a weighting function the Gaussian function is used. The parameters of the Gaussian function were chosen either without or with optimization of the identification cost function. The global valid nonlinear model was used for model based predictive control. A heat exchanger example illustrates the method. © 2003 IFAC.

关键词： Heat exchangers

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Optimal choice of horizons for predictive control by using genetic algorithms 2

Optimal choice of horizons for predictive control by using g...

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2nd IFAC Conference on control Systems Design, CSD 2003

作者： Haber, R. Schmitz, U. Bars, R. Department of Plant and Process Engineering Laboratory of Process Control University of Applied Science Cologne Betzdorfer Str. 2 KolnD-50679 Germany Department of Automation and Applied Informatics Budapest University of Technology and Economics Goldmann Gy. ter 3 BudapestH-1111 Hungary

For predictive control in industry often very long horizons for control error and manipulated signal are used because of the slow processes which take place in the petrochemical industry. In order to reduce the computational effort some commercial predictive control program packages offer the ability to reduce the number of points in both horizons but do not recommend how to select the points which have to be considered in the horizon of the control error and manipulated variable. in this work the authors introduce an optimal choice not only of the horizon lengths itself but also for the strategy of reducing the number of points in the horizons. A genetic optimization algorithm was used both for the search for the optimal length of the horizons and for the best allocation of the points in the horizons. The results of the optimization process where used to deduct a simple rule. © 2003 IFAC.

关键词： Genetic algorithms

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Hybrid IMC dead-beat controller design in delta domain 2

Hybrid IMC dead-beat controller design in delta domain

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2nd IFAC Conference on control Systems Design, CSD 2003

作者： Preit, Z. Bars, R. Vajk, I. Haber, R. Department of Automation and Applied Informatics Budapest University of Technology and Economics MTA-BME Control Research Group Goldmann Gyter 3 BudapestH-1111 Hungary Department of Plant and Process Engineering University of Applied Science Cologne Germany

The paper presents a control system design technique in delta domain for IMC (Internal Model control) structure. Also a generalised form for delta domain Dead-beat control algorithm is given, a hybrid implementation of the controller (Z-domain combined with delta domain) is presented and its architecture is compared with the pure deltadomain implementation. The effect of placing the limitations in the IMC structure is also studied. The hybrid control structure is compared with a similar Dead-beat controller in Z-domain for second and third order plants (benchmarks). An illustrative sensitivity analysis between the hybrid control system and the Z-domain system has been performed. © 2003 IFAC.

关键词： controllers

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Near minimax robust control of flexible structures

Near minimax robust control of flexible structures

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American control Conference (ACC)

作者： M. Muenchhof T. Singh Department of Mechanical and Aerospace Engineering SUNY at Buffalo Buffalo NY USA Institute of Automatic Control Laboratory of Control Systems and Process Automation Darmstadt University of Technology Darmstadt Germany

This paper presents an approach to calculate prefilters that are insensitive to parameter deviations. The cost function chosen for this approach is the magnitude of the time-delay filter transfer function. By approximating the cost function with a polynomial, the effort of calculating minimax robust profiles can be reduced. The resulting control profiles yield a performance similar to the minimax robust controller. This is verified by the numerical results included in this paper.

关键词： Minimax techniques Robust control Flexible structures Filters Uncertainty Frequency Cost function Vibrations control systems Delay effects

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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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Operator Support System for the Larox Pressure Filter

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IFAC Proceedings Volumes 2003年第24期36卷 245-250页

作者： S-L. Jämsä-Jounela M. Vermasvuori J. Kämpe A. Kesti Kari Koskela Helsinki University of Technology Department of Chemical Technology Laboratory of Process Control and Automation Kemistintie 1. FIN-02150 Espoo FINLAND Larox Corporation P.O. Box 2953101 Lappeenranta FINLAND

关键词： Expert systems Optimisation problem Fault detection Computer applications and Models

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Optimal Choice of Horizons for Predictive control by Using Genetic Algorithms

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IFAC Proceedings Volumes 2003年第18期36卷 507-512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 Budapest University of Technology and Economics H-1111 Budapest Goldmann Gy. tér 3. Hungary fax : +36-1-463-2871

For predictive control in industry often very long horizons for control error and manipulated signal are used because of the slow processes which take place in the petrochemical industry. In order to reduce the computational effort some commercial predictive control program packages offer the ability to reduce the number of points in both horizons but do not recommend how to select the points which have to be considered in the horizon of the control error and manipulated variable. In this work the authors introduce an optimal choice not only of the horizon lengths itself but also for the strategy of reducing the number of points in the horizons. A genetic optimization algorithm was used both for the search for the optimal length of the horizons and for the best allocation of the points in the horizons. The results of the optimization process where used to deduct a simple rule.

关键词： Predictive control long horizons blocking coincidence points compaction points optimal choice of horizons

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Hybrid IMC Dead-Beat controller Design in Delta Domain

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IFAC Proceedings Volumes 2003年第18期36卷 381-386页

作者： Zs. Preitl R. Bars I. Vajk R. Haber Department of Automation and Applied Informatics Budapest University of Technology and Economics. MTA-BME Control Research Group H-1111 Budapest Goldmann Gy. tér 3. Hungary: fax : + 36-1-463-2871 Department of Plant and Process Engineering University of Applied Science Cologne Germany

关键词： controller design delta domain generalised hybrid Dead-beat controller sensitivity analysis

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