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 contr...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.展开更多
This paper investigates a global asymptotic regulation control problem for a class of nonlinear systems with dynamic uncertainties.The requirement of a priori knowledge of control directions is removed and the inverse...This paper investigates a global asymptotic regulation control problem for a class of nonlinear systems with dynamic uncertainties.The requirement of a priori knowledge of control directions is removed and the inverse dynamics satisfy the weaker integral input-to-state stable condition.By application of the changing supply rates and the Nussbaum-type gain techniques,a partial state-feedback regulator is constructed.The main results demonstrate that the designed controller ensures the system state converges to the origin whereas the other signals of the closed-loop system are bounded. Simulation results are illustrated to show the effectiveness of the proposed approach.展开更多
基金National Natural Science Foundation of China(Nos.62171285,61971120 and 62327807)。
文摘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.
基金supported by the National Natural Science Foundation of China under Grant Nos.60674027, 60974127,and 60904022the Key Project Foundation of the Educational Ministry under Grant No.208074the Innovation Program of Graduate Students of Jiangsu Province of China under Grant No.CXZZ11_0155
文摘This paper investigates a global asymptotic regulation control problem for a class of nonlinear systems with dynamic uncertainties.The requirement of a priori knowledge of control directions is removed and the inverse dynamics satisfy the weaker integral input-to-state stable condition.By application of the changing supply rates and the Nussbaum-type gain techniques,a partial state-feedback regulator is constructed.The main results demonstrate that the designed controller ensures the system state converges to the origin whereas the other signals of the closed-loop system are bounded. Simulation results are illustrated to show the effectiveness of the proposed approach.
