Control of a hydraulic system by means of a fuzzy approach

Abstract

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.

Design of Fuzzy TS-PDC Controller for Electrical Power System via Rules Reduction Approach

“…This technique is based on considering some nonlinearities as uncertainties in the system model [16,21,[24][25][26][27].…”

“…By considering the following property [21]: Then Equation (35) would be written in the following form:…”