ABSTRACT
This chapter aims to design a stiffness test machine for different car components, examines a mathematical model, and describes the relevant control strategy. It argues that the Radial Basis Function (RBF) neural network PID method can achieve stable control with a small overshoot, fast response, high stability, and short time. The chapter explores the MATLAB to simulate the RBF neural network PID and traditional PID. A PID control method based on RBF neural network is put forward, which can make use of neural network learning to adjust the parameters of PID according to the actual situation. RBF neural network PID can get its best PID parameters when testing each kind of different car component. RBF neural network simulates the structure of the neural network in the human brain, and it is a kind of local approximation network, which can approximate any continuous function with any precision.
