Positioning Control of Piezoelectric Stick-slip Actuators Based on Single Neuron Adaptive PID Algorithm

Abstract

Aiming at the problem of large positioning control error caused by the change of starting and ending position of piezoelectric stick-slip actuators, an adaptive PID full closed loop control method based on single neuron is proposed in this paper. Firstly, the dynamic model of the spring damping system is adopted, and the LuGre friction model is introduced to represent the stick-slip relationship between the drive block and the friction rod. Then, the adaptive PID full closed-loop control scheme based on single neuron and the principles of traditional PID algorithm and variable speed integral PID control algorithm are analyzed. The proposed control method is simulated and compared with the other two methods by MATLAB software. Finally, the effectiveness of the proposed method is verified by an experimental platform. The experimental results show that the maximum positioning errors of the proposed control method and the other two methods are 180 nm, 270 nm and 280 nm, respectively, when the desired position is 1 mm in low-frequency motion. Under the same experimental conditions, the proposed control scheme shows high control accuracy when the starting and ending position changes.