Modeling And Compensation Of Hysteresis In Piezoelectric Actuator

Along with the fast development of ultra-precision motion systems, model and con-trol of piezoelectric actuators draw significant research interest. Unfortunately, one of the main obstacles hindering their applications is the hysteresis, which is not ignorable in ap-plications that require a high accuracy in motion control. To address such challenges, this dissertation presents a comprehensive modeling, controller design and experimental evalu-ation for piezoelectric actuators with complex hysteresis nonlinearity. With the emerging applications of piezoelectric material based actuated system, the results of the dissertation will enrich the theory and methodology of hysteresis compensation and control, and advance the state of nanomanufacturing in both theoretic and practical aspects. The main research contents and achievements are listed as follows.A modified asymmetric Bouc-Wen model is proposed for modeling the nonlinear hys-teresis behavior in piezoelectric actuator. By employing particle swarm optimization (PSO) approach, all parameters of the proposed model are identified simultaneously with high pre-cision and high efficiency. The validity of the proposed model is experimentally testified in comparison with the classical Bouc-Wen model to demonstrate its effectiveness on the hys-teresis prediction. For the controller design, a new approach based on PSO for linearizing the hysteretic nonlinear term is presented. On the basis of the proposed model, an H∞full order output feedback robust controller utilizing almost disturbance decoupling is develope-d. Experiments shown that the developed controller can cancel the nonlinear hysteresis in piezoelectric actuator effectively.Considering rate-dependent property of piezoelectric actuator, this dissertation further proposes an asymmetric rate-dependent Bouc-Wen model. In order to avoid laborious math-ematical procedure for constructing an inversion of the hysteresis model, a new digital in-verse controller with a simple structure cascaded in the feedforward path for piezoelectric actuator is developed. Experimental results demonstrate that the proposed model together with the developed inverse control scheme have shown significantly reduced tracking errors caused by asymmetric rate-dependent hysteresis in piezoelectric actuator.A nonlinear autoregressive moving average with exogenous inputs (NARMAX) model based on backpagation (BP) neural network is proposed for modeling the nonlinear hys-teresis behavior in piezoelectric actuator. In order to demonstrate the precision and the rate-dependent property of the proposed model, experiments are performed under designed excitations with different amplitudes and frequencies. Furthermore, taking advantage of the proposed model, a nonlinear controller based on adaptive inverse control for the compen-sation of hysteresis in the piezoelectric actuator is designed. Experiments are conducted to validate the performance of the developed control system. Experimental results confirm that the tracking performance could reach a precision as accurate as ten nanometer order.This dissertation also presents the design, modeling, calibration and hysteresis compen-sation of a smart stage. Aiming at an extremely compact structure, a self-sensing actuator called smart piezo-stack which is capable of not only producing high-solution displacement but also monitoring the dynamic characteristics of the proposed stage is designed and fabricated. By means of the finite element analysis (FEA) and experimental measurements, the crosstalk phenomenon in the smart piezo-stack is revealed and quantitatively analyzed. After calibrating the sensitivity of the smart piezo-stack experimentally, the dynamics model of the proposed stage is established. Furthermore, a NARMAX model based on BP neural network is developed to design a nonlinear controller based on adaptive inverse con-trol. Experimental validation of the adaptive inverse controller is conducted and the results demonstrate the effectiveness of the proposed mechanism and the developed control system.