A Hybrid Compensation Scheme for the Input Rate-Dependent Hysteresis of the Piezoelectric Ceramic Actuators

Abstract

A hybrid compensation scheme for piezoelectric ceramic actuators(PEAs)is proposed. In the hybrid compensation scheme, the input rate-dependent hysteresis characteristics of the PEAs are compensated. The feedforward controller is a novel input rate-dependent neural network hysteresis inverse model, while the feedback controller is a proportion integration differentiation(PID)controller. In the proposed inverse model, an input ratedependent auxiliary inverse operator(RAIO)and output of the hysteresis construct the expanded input space(EIS)of the inverse model which transforms the hysteresis inverse with multi-valued mapping into single-valued mapping, and the wiping-out, rate-dependent and continuous properties of the RAIO are analyzed in theories. Based on the EIS method, a hysteresis neural network inverse model, namely the dynamic back propagation neural network(DBPNN)model, is established. Moreover, a hybrid compensation scheme for the PEAs is designed to compensate for the hysteresis. Finally, the proposed method, the conventional PID controller and the hybrid controller with the modified input rate-dependent Prandtl-Ishlinskii(MRPI)model are all applied in the experimental platform. Experimental results show that the proposed method has obvious superiorities in the performance of the system.

Keywords

hybrid control / input rate-dependent hysteresis / inverse model / neural network / piezoelectric ceramic actuator

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Funding

National Natural Science Foundation of China(62171285)

National Natural Science Foundation of China(61971120)

National Natural Science Foundation of China(62327807)