The Optimizing Design of Wheeled Robot Tracking System by PID Control Algorithm Based On BP Neural Network

The tracking system of robot was optimized by using the fuzzy BP neural network PID control algorithm in this paper, which was based on the traditional PID control algorithm. The control algorithm combines the functions of fuzzy control, the neural network control and the traditional PID control algorithm, which resulted The PID control has the ability of logical reasoning and computing. The system collects the scheduled route information through the sensor module and altogether with the actual output of the system constitute the excitation signal of the neural network. The MATLAB software is used to simulate the system in this paper, compared with the result of the simulation of traditional PID control algorithm. The result shows that optimize design of wheeled robot tracking system with PID control algorithm based on BP neural network has better adaptive ability and self-learning ability and the improvement of the stability of wheeled robot tracking system.