Fuzzy optimal control of nonlinear systems

This work is aimed at looking into the fuzzy optimal control of nonlinear systems detailing adopted mechanisms and approaches in order to be able to control these systems. First of all, the nonlinear systems have been modeled by Sugeno fuzzy systems. Then, three approaches have been considered. In the first one, a local approach to obtain fuzzy models has been applied. The second one is a global fuzzy optimal control procedure. The third one consists in the use of genetic algorithms to optimize parameters of fuzzy controllers. At the end of this work, a comparative study between considered approaches has been presented. It has been found that (i) the global approach gives better results, (ii) the optimized fuzzy controller by genetic algorithms presents a slight sub-optimality, and (iii) the local approach gives also a slight sub-optimality.