Remodeling of fuzzy PID controller based on BP neural network

The combination of widely-used PID controller with fuzzy system generates fuzzy PID controller which possesses excellent control quality. However, the fuzzy PID controller has some problems of computation complexity and real-time performance. To solve these problems, the paper expounds the process of training BP neural network through its universal function approximating ability and PID controllerpsilas input and output couple. Simulation researches reveal that the fuzzy PID controller can be effectively replaced by the trained BP neural network. Therefore, the method can simplify the computation complexity, enhance the real-time performance of fuzzy PID controller, and promote its implementation by hardware.