基于迭代学习算法的电液比例伺服控制

In order to solve the problem of nonlinearity, time-varying, variable flow dead zone and variable flow gain of electro-hydraulic proportional control system, and improve the control precision of electro-hydraulic proportional control system, an iterative learning algorithm that does not strictly depend on the exact mathematical model of the system is designed. At the same time, according to the variable dead zone characteristic of the system, a fuzzy dead-band compensation algorithm is proposed to adjust the dead zone compensation based on error and error rate of change. The combination of iterative learning algorithm and fuzzy dead zone compensation algorithm is based on the current control experience to flexibly adjust the control volume, thus effectively improving the system's control performance. The experimental results show that there is a significant lag in system location tracking without fuzzy dead-band compensation, the maximum displacement tracking error is 6 mm; the control performance of the system is improved by using of the iterative learning algorithm and the fuzzy dead-band compensation algorithm. After the system achieved stable tracking, the maximum displacement tracking error is less than 1 mm.