Research on PID controller based on the BP neural network

Abstract

The BP neural network is a multilayer feedforward network which spreads error inversely, the BP network can learn and store a lot of input/output mapping relationship without prior reveal the mathematical equations. The learning rule is to use the steepest descent method, the weights and threshold of network are adjusted constantly by the back propagation, which makes the network error squares minimum. Neural network with arbitrary nonlinear expression ability can realize the PID control which has the best combination by studying system performance, by the BP network, the parameters Kp , Kj , K^ self-learning PID controller can been built, the simulation results show that the system has good dynamic and static performance. KeywordsBP neural network; PID control; self-learning