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IEEE Conference on Decision and control

作者： D. Henrion J. Lofberg M. Kocvara M. Stingl LAAS CNRS Toulouse France Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Automatic Control Laboratory Swiss Federal Institute of Technology Zurich Switzerland Institute of Information Theory and Automation Academy of Sciences슠of the슠Czech Republic Prague Czech Republic Institute of Applied Mathematics University of Erlangen Erlangen Germany

An algebraic formulation is proposed for the static output feedback (SOF) problem: the Hermite stability criterion is applied on the closed-loop characteristic polynomial, resulting in a non-convex bilinear matrix inequality (BMI) optimization problem for SIMO or MISO systems. As a result, the BMI problem is formulated directly in the controller parameters, without additional Lyapunov variables. The publicly available solver PENBMI 2.0 interfaced with YALMIP 3.0 is then applied to solve benchmark examples. Implementation and numerical aspects are widely discussed.

关键词： Polynomials Output feedback Linear matrix inequalities Stability criteria Eigenvalues and eigenfunctions control engineering Lagrangian functions Automatic control Laboratories Information theory

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Nonlinear process identification and predictive control by multi-parameter models 6

Nonlinear process identification and predictive control by m...

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6th IFAC Symposium on Nonlinear control Systems, NOLCOS 2004

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

According to the multi-model approach a nonlinear dynamical process is approximated in different working points by local valid linear models. The global valid model output is calculated as the weighted sum of the sub-model outputs. The parameters of the Gaussian weighting function can be chosen by optimization. The computation time can be reduced if instead of the model outputs the parameters (for example static gain and time constant) of the local valid models are merged. The global valid nonlinear model can be used e.g., for model based predictive control. The new, multi-parameter method is illustrated by a heat exchanger example. Copyright © 2004 IEAC.

关键词： Heat exchangers

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Multilevel validation of online monitor for hard real-time systems

Multilevel validation of online monitor for hard real-time s...

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International Conference on Microelectronics, MIEL

作者： M. Jevtic V. Zerbe S. Brankov Department of Electronics. Faculty of Electronic Engineering University of Nis Nis Serbia Department of System and Control Theory Faculty of Automation and Informatics Technische Universität llmenau Llmenau Germany

To achieve the required performance of complex electronic systems it is necessary to validate the system function during all phases of the design, which means multilevel validation. A hybrid Online Monitor for hard real time systems (HRTS) has been developed. A special attention was dedicated on the multilevel validation in all phases of the design.

关键词： Monitoring Real time systems Hardware System testing Kernel Runtime Automotive engineering Electrical equipment industry Automobiles Circuit faults

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Modeling Demand for Inventory Management of Slow-Moving Items in Case of Reporting Errors

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IFAC Proceedings Volumes 2004年第4期37卷 27-32页

作者： Alexandre Dolgui Anatoly Pashkevich Maxim Pashkevich Scientific Methods for Industrial Management Dept. (MSGI) Industrial Engineering and Computer Sciences Center (G2I) Ecole de Mines de Saint Etienne 158 Cours Fauriel 42023 Saint Etienne France Robotic Laboratory Department of Automatic Control Belarusian State University of Informatics and Radioelectronics 6 P.Brovka St. Minsk 220027 Belarus Department of Mathematical Modeling and Data Analysis Faculty of Applied Mathematics and Computer Science Belarusian State University Skarina Av. 4 Minsk 220050 Belarus

The paper is devoted to the problem of modeling demand for inventory management of slow-moving items in the case of reporting errors. It is proposed a generalization of the beta-binomial demand model that takes into account possible reporting errors in the learning sample. For the new model, there are developed identification and forecasting algorithms that provide consistent estimators of the model parameters and mean square optimal forecasts. The efficiency of the proposed approach is illustrated by an application example for slow-moving car parts.

关键词： inventory control error correction statistical inference parameter estimation prediction methods

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Direct learning control design for a class of linear time-varying switched systems

Direct learning control design for a class of linear time-va...

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Fourth International Conference on control and automation

作者： Xu, Jian-Xin Korondi, Peter Yan, Rui Guan, Zhi-Hong Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Department of Automation and Applied Informatics Budapest University of Technology and Economics Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)078037777X

In this paper, a direct learning control method for a class of switched systems is proposed. The objective of direct learning is to generate the desired control profile for a newly switched system without any feedback, even if the system may have uncertainties. This is achieved by exploring the inherent relationship between any two systems before and after a switch. The new method is applicable to a class of linear time varying, uncertain and switched systems, when the trajectory tracking control problem is concerned. A numerical simulation demonstrates the effectiveness of the proposed method. © 2003 IEEE.

关键词： Time varying control systems

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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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Long-range optimal model and multi-step-ahead prediction identification for predictive control 13

Long-range optimal model and multi-step-ahead prediction ide...

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13th IFAC Symposium on System Identification, SYSID 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 KölnD-50679 Germany Department of Automation and Applied Informatics Control Research Group 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. © 2003 International Federation of Automatic control.

关键词： Parameter estimation

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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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Synchronous machine-turbine drive system with indirect speed control

Synchronous machine-turbine drive system with indirect speed...

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IEEE International Conference on Electric Machines and Drives (IEMDC)

作者： R.K. Jardan I. Nagy Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Budapest University슠of슠Technology슠and슠Economics Budapest Hungary Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Dynamic properties of a hybrid system are analyzed that has been developed to generate electric energy by utilizing alternative, renewable and waste energies. The solution is based on a system that consists of a high-speed turbine, coupled to a three-phase permanent magnet synchronous generator, an AC/AC converter and a supervisory control unit. The function of the system is to utilize the energy content of some working medium by a special turbine that converts the energy content of the working medium into electric energy by the generator and the AC/AC converter. The alternative renewable energy sources may include solar energy (direct solar steam system or solar energy with heat exchanger), geothermal energy (with or without heat exchanger) and energy obtained from biomass. Various waste energy sources can also be utilized by applying the system such as the energy that can be obtained during the process of pressure reduction in steam, gas and fluid networks. The electric power generated by the system can be fed back to the utility mains or it can be used in stand-alone mode to supply a selected group of loads. The paper analyses a novel control strategy and principle of the system to ensure optimum performance and economy by using a special solution for ensuring the power equilibrium in the combined mechanical-electric drive.

关键词： Velocity control Turbines Geothermal power generation Solar energy Solar heating Magnetic analysis Hybrid power systems Couplings Permanent magnets Synchronous generators

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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

关键词： Process identification prediction parameter estimation predictive control

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