基于Smith预估补偿与RBF神经网络的PID控制在工业平缝机脚踏板调速模块中的应用

针对工业缝纫机调速模块的伺服系统普遍存在耦合,大滞后的现象,提出了一种将Smith预估补偿和RBF神经网络算法与PID控制器相结合的Smith-RBF-PID控制算法。该方法利用了Smith预估补偿能克服纯滞后和RBF能处理非线性问题、在线自学习整定PID参数的优点,在调速模块的伺服控制系统中更加有效。

Application of Industry Sartorius Foot Speed Regulation Module on PID Control Based on Smith Predictive Compensation and RBF Neural Network

Aiming at the phenomena of coupling and big time delay existed in industry Sartorius foot speed regulation module servo system, this paper proposed a Smith-RBF-PID control method based on Smith pre- dictive compensation algorithm and RBF neural network algorithm and PID controller. This method uses the advantage of Smith predictive compensation to overcome big time delay, and the ability of deal with non-linear problem, a self-turning control strategy of RBF neural network. It is more effective in speed reg- ulation module servo system.