Parameter Identification And Adaptive Sliding Mode Control Of Nonlinear Servo System

Nonlinear servo systems are widely used in many practical control fields,such as industrial robots,aerospace and laser processing equipment.Such systems are often accompanied by nonlinear friction,parameter perturbation and external disturbances.In the control strategy of servo system,sliding mode control has been widely studied because of its good control effect on the above uncertainties.However,this control method needs to establish a high-precision mathematical model of the servo system,otherwise it will easily lead to chattering phenomenon,which limits the practical application of the control method.The adaptive identification law of parameters can realize real-time feedback to the perturbation caused by the change of external parameters of the system.Therefore,a reasonable identification law can be designed to make the parameters converge to the actual value quickly and accurately,which can effectively improve the control performance of the system.Therefore,an adaptive sliding mode control strategy combining adaptive parameter identification method with sliding mode control theory is proposed in this paper to solve the uncertainties such as friction,parameter change and external disturbance of the system.At the same time,it also aims to improve the control performance and parameter identification accuracy of the system,and reduce the jitter amplitude of the control signal.Therefore,this subject proposes an adaptive sliding mode control strategy that combines the adaptive parameter identification method and sliding mode control theory to solve the uncertainty of system friction,parameter changes,and system external disturbances.It improves the control performance and parameter identification accuracy of the system,and weakens the jitter amplitude of the system control signal.The specific research content and detailed work done on this subject are as follows:(1)Aiming at a kind of nonlinear servo system with unknown friction parameters and parameter perturbation,an adaptive sliding mode control strategy based on simulated annealing cuckoo algorithm(SACA)is designed.The SACA algorithm is used to identify the static and dynamic parameters in the friction model of the system,and the more accurate friction model parameters of the servo system were obtained.Using the introduced state observer and the estimated error value,an adaptive parameter identification law is designed to give real-time feedback to the friction parameters of the system,which effectively solves the problem that the parameters cannot converge quickly due to the perturbation of model dynamic parameters.Using the introduced nonlinear sliding mode surface,an adaptive sliding mode controller is designed according to the position tracking error defined by the servo system,and its stability is proved.(2)Considering that part of the state of the nonlinear servo system is unknown,and it is also affected by many factors such as nonlinear friction,operating environment,and external disturbance,the research is based on the extended state observer(ESO),combined with the idea of adaptive law,designing an adaptive sliding mode controller to control the servo system.First of all,in order to make the ESO parameter gain tuning process simpler,the pole configuration method is used to derive the tuned ESO.And use the observer to accurately estimate the system state variables,avoiding the situation where the controller cannot be designed due to the unknown system state.At the same time,the controller is designed according to the estimation result of ESO to ensure that the servo system can quickly and accurately track the reference signal.Through the comparison of simulation examples,the tracking performance,robust performance and chattering elimination ability of the proposed control strategy are verified.(3)Based on the above research,an adaptive sliding mode control strategy is designed for nonlinear servo systems with unmeasurable and disturbing friction parameters by introducing a new approach law constructed by power function and inverse hyperbolic sine function.Firstly,according to the unmeasurable parameters in the system,and by filtering the regression matrix in the friction model,an adaptive parameter identification law is designed to realize the accurate identification of its parameters.Secondly,the disturbance observer is designed to effectively observe and compensate the disturbance signal and identification error.Finally,the adaptive sliding mode controller designed by introducing a new reaching law reduces the amplitude of the system control signal chattering.