变比例双向拉压实验机智能控制系统研究

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

针对双向抗压实验机在塑性板材抗压实验中存在的PID控制参数调整繁琐的问题,该文在PID控制的基础上,设计了BP神经网络PID控制器,通过对双向拉压实验机的四轴进行同步变比例控制来减小电机之间的速度波动。同时使用Matlab软件建立电机的输入输出传递函数模型并进行仿真实验与验证,仿真结果表明:相比传统的PID控制,BP神经网络PID控制具有更快的调速性能和收敛速度,通过设备验证其有更好的控制效果。

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.