An efficient vibration suppression technology of piezoelectric cantilever beam based on the NARX neural network

Abstract

Low-frequency vibration is the core problem that hinders high-precision equipment’s positioning accuracy and control accuracy. However, the response of a nonlinear electrical-mechanical coupling system is nonlinear and quite complicated under the ambient random vibrating environment. This paper presents a vibration suppression method through NARX (Nonlinear autoregressive with external input) neural network and its controller. The experiment platform is designed, and its dynamic model is obtained through system identification. The Neural network direct dynamic inverse control system is established, and the controller is designed. Both the simulation and experimental results show that the NARX identification and the controller can effectively achieve vibration suppression, and the experiment’s highest vibration rejection ratio is 90.8%. The vibration suppression technology can be extensively applied to low-frequency vibration systems, such as aerospace equipment and high-precision equipment.