Smith-RBF-PID控制算法在工业平缝机脚踏板调速模块中的应用

Application of PID Control Algorithm in Industrial Sewing Machine Pedal Speed-Regulation Module Based on Smith Predictive Compensation and RBF Neural Network

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。

In view of the phenomena of coupling and big time delay in the servo system of the industrialsewing machine pedal speed - regulation module, a Smith - RBF - PID control algorithm was proposedbased on Smith predictive 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 that ofRBF to deal with non - linear problems, and that of a self - turning control strategy of RBF neural net-work, which makes the speed -regulation module servo system more efficient.