Adaptive Dynamic Surface Output Feedback Control Strategy For Nonlinear Systems And Its Application

In recent years,the adaptive dynamic surface control method has been at the forefront of the control field.Because it solves the problem of"explosion of complexity"in the backstepping control method,it has been widely concerned by scholars in the field of control.With the gradual deepening of state feedback research,more and more results stand out.However,in practical problems,most of the controlled objects are nonlinear,and only the output signal can be measured,and other states are unknown.Therefore,the research on nonlinear output feedback has a strong practical significance.In this thesis,an adaptive dynamic surface output feedback control strategy for nonlinear systems is proposed and applied to the control of intelligent material drives.The control strategy is verified by experimental simulation.The main research results are as follows:(1)A decentralized neural adaptive dynamic surface approximated inverse control scheme is proposed for a class of large-scale time-delay systems with hysteresis nonlinearities as input.The decentralized control problem under the case only the outputs are measurable is solved by utilizing the radial basis function neural networks approximator and the hysteresis approximated inverse compensator.Also,with the help of finite covering lemma,the traditional Krasovskii functionals are dropped when coping with the delays,leading to the removal of the assumptions on the functions with time-delay states and the acquisition of the arbitrarily small L_?tracking performance of each hysteretic subsystem with time delays.The analysis of stabilities guarantees all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded.Simulation results illustrate the efficiency of the proposed scheme.(2)Focusing on the piezoelectric positioning stage,an adaptive estimated inverse output-feedback quantized control scheme is proposed.First,the quantized issue due to the use of computer is addressed by introducing a linear time-varying quantizer model where the quantizer parameters can be estimated on-line.Second,by using the fuzzy approximator,the developed controller can avoid the identification of the parameters in the piezoelectric positioning stage.Third,by constructing the estimated inverse compensator of the hysteresis,the hysteresis nonlinearities in the piezoelectric actuator are mitigated;Fourth,the states observer is designed to avoid the measurements of the velocity and acceleration signals.The analysis of stability shows all the signals in the piezoelectric positioning stage are uniformly ultimately bounded and the prespecified tracking performance of the quantized control system is achieved by employing the error transformed function.Finally,a computer controlled experiments for the piezoelectric positioning stage is conducted to show the effectiveness of the proposed quantized controller.