An adaptive Fuzzy Cerebellar Model Articulation Controller via Particle Swarm Optimization

In the paper, a Fuzzy Cerebellar Model Arithmetic Controller (FCMAC) is proposed to solve the tracking problems of a class of nonlinear systems. First, the proposed FCMAC via parameters adaptation such that it is able to approximate an ideal controller, and then a robust controller is appended to assure the system stability in the present of approximated error. Third, the redesign of the proposed FCMAC promotes the performances of the closed-loop system. Moreover, to further optimize the redesigned FCMAC, the Particle Swarm Optimization (PSO) is utilized to optimize the parameters of the proposed FCMAC under the requirements of system stability and the defined performance index. From the computer simulation results we can find that the performances of the system are promoted under the proposed control scheme.