Abstract: Considering the problems of the linearity limit of PID control and the steady-state error in fuzzy, fuzzy PID control for it cannot easily obtain the control rules of the integral error, so a fuzzy neural PID controller which consists of a fuzzy neural network and a PID neural network is designed. The parameters of the controller are optimized by the mixed learning methods integrating the offline particle swarm optimization algorithm combined with chaos strategies of global searching ability, with the online BP algorithm of local searching ability. Simulation results show that the designed novel controller and the proposed optimization algorithm have obviously improved the performance of the transient state and steady state in the control processing. Compared with conventional PID, fuzzy control and fuzzy-PID control method, the new controller with the optimization method has good robustness and better performance. The new method breaks through the limit of linearity of PID control and expands its applications. It also provides a new reference for the combination of intelligent method and PID method.

Key words: steady-state error, PID neural network, fuzzy neural PID controller, chaos optimization, particle swarm optimization