Hysteresis Neural Network Modeling and Compensation of Piezoelectric Actuator

Abstract:

By studying on the nonlinear hysteresis characteristics of piezoelectric actuators,this paper proposes a neural network modeling method based on polynomial fitting algorithm and a compound control method for compensation of the hysteresis.Simulation shows that the fitting error of neural network model is 1.42%. According to the developed hysteretic model,PID and feed-forward control methods are applied to the system.The result is that the tracking relative error of control system is 1.59%,so the tracking precision of system is improved significantly.This indicates that the neural network model reflects the hysteresis characteristics of piezoelectric actuators accurately,and this control method is an effective compensation control for hysteresis in piezoelectric actuators.

• Periodical: Applied Mechanics and Materials (Volumes 635-637)
• Pages: 1426-1430
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.635-637.1426
• Online since: September 2014
• Authors: Fei Qian, Zhen Wu Guo, Su An Xu*, Gui Rong Wang, Yun Tang Li
• Keywords: Compensation Control, Hysteresis Nonlinearity, Neural Network (NN), Piezoelectric Actuator, Polynomial Fitting

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