Control of a Nonlinear System by Fuzzy Supervision. A Local Approach

The aim of this paper is to present a general method of a nonlinear control system by fuzzy supervision of a conventional control. This approach belongs to the class of methods based on the use of the linearized system. The particularity of this work lies in the proposed algorithms to realize the parametric adaptation of control law and running equilibrium estimation. These two aspects have been solved by the use of a fuzzy supervisor based on a Takagi-Sugeno rules. The rules bases are built by the knowledge of the gains and the equilibrium, for a fixed number of operating points. The gains are calculated using a local synthesis by poles placement. The implementation of this method is presented on a real example for which a generator of reference trajectory is presented. The results available are compared with the ones obtained by use of Isidori linearizing control method and lead to the validation of this method.