From differential equations to PDC controller design via numerical transformation

Authors:
Péter Baranyi;Domonkos Tikk;Yeung Yam;Ron J. Patton
Affiliations:
Department of Telecommunications and Telematics, Budapest University of Technology and Economics and Integrated Intelligent Systems Japanese-Hungarian Laboratory, H-1111 Budapest, Hungary;Department of Telecommunications and Telematics, Budapest University of Technology and Economics and Integrated Intelligent Systems Japanese-Hungarian Laboratory, H-1111 Budapest, Hungary;Department Automation and Computer Aided Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;Control and Intelligent Systems Research Group, University of Hull, Cottingham Road, Hull HU6 7RX, UK
Venue:
Computers in Industry
Year:
2003

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Abstract

This paper proposes a transformation method capable of transforming analytically given differential equations of dynamic models into Takagi-Sugeno fuzzy inference model (TS fuzzy model), whereupon various parallel distributed compensation (PDC) controller design techniques can readily be executed. Joining the transformation method and the PDC techniques leads to a controller design framework. The transformation method is specialized to minimize the number of fuzzy rules in the resulting TS fuzzy model according to a given acceptable transformation error, the PDC design thus results in a computational complexity minimized controller which is highly desired in many cases of real applications. The paper presents examples to show the effectiveness of the proposed transformation.