Design of optimal fuzzy logic controller with genetic algorithms

This paper looks into the determination of optimal trajectories of a nonlinear model of a two-link articulated manipulator. In a first step, genetic algorithms are used to generate an optimal control sequence which is used to bring the manipulator robot into a desired position. In a second step, genetic algorithms optimize the parameters of membership functions to facilitate the realization of a Sugeno fuzzy logic based optimal controller. Simulation results show that the second step gives suboptimal solutions, however the first step yields to optimal solutions which are very sensitive with respect to the parameter variation of the system.