Research on Intelligent Control System of Variable Ratio Bidirectional Tension and Compression Experiment

In order to study the mechanical properties of plastic sheets under bidirectional tension and compression, a bidirectional tension and compression testing machine is needed. Currently, its control system is mainly PID control, but the adjustment of PID control parameters is relatively cumbersome. In response to this problem, a BP neural network PID controller is designed in this paper based on PID control, which synchronizes and proportionally controls the four axes of the bidirectional tension and compression testing machine to reduce speed fluctuations between motors. The input output transfer function model of the motor is established by using the Matlab software. The simulation results shows that the BP neural network PID control has faster speed regulation performance and convergence speed compared to the traditional PID control, and its better control effect is verified through the equipment verification.