Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm

This paper tackles the control problem of nonlinear systems subject to parameter uncertainties based on the fuzzy logic approach and genetic algorithm (GA). In order to achieve a stable controller, the TSK fuzzy plant model is employed to describe the dynamics of an uncertain nonlinear plant. A fuzzy controller and the corresponding stability conditions are derived. The parameters of the fuzzy controller and the solution to the stability conditions are determined using GA. In order to obtain the optimal performance, the membership functions of the fuzzy controller are obtained automatically by minimizing a defined fitness function using GA.