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Control of a hydraulic system by means of a fuzzy approach
Author(s) -
Mohamed Ksantini,
Ameni Ellouze,
François Delmotte
Publication year - 2013
Publication title -
an international journal of optimization and control theories and applications (ijocta)
Language(s) - English
Resource type - Journals
eISSN - 2146-5703
pISSN - 2146-0957
DOI - 10.11121/ijocta.01.2013.00153
Subject(s) - control theory (sociology) , bounded function , linear system , mathematics , interpolation (computer graphics) , lyapunov function , nonlinear system , stability (learning theory) , linear interpolation , fuzzy logic , exponential stability , linear model , fuzzy control system , computer science , mathematical optimization , control (management) , polynomial , artificial intelligence , motion (physics) , mathematical analysis , statistics , physics , quantum mechanics , machine learning
Non linear models can be represented conveniently by Takagi-Sugeno fuzzy models when nonlinearities are bounded. This approach uses a collection of linear models which are interpolated by non linear functions. Then the global control law is the interpolation by the same functions of each feedback associated to each linear model. A Lyapunov approach enables to compute these feedback gains. The number of linear models depends directly on the number of nonlinearities the system has. The more models there are, the more difficult it is to guarantee the stability of the closed loop. This paper proposes a method to reduce the number of linear models by assuming a number of nonlinearities considered as uncertainties and to guarantee the global exponential stability of the system. This method is applied on a hydraulic system.

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