Limited-time Adaptive Fuzzy Control Of Asynchronous Motor Based On Command Filtering

In the past few decades,the induction motors(IMs)are widely used in the field of industry with its advantages of cheap price,simple structure,high reliability and durability.With the rapid development of modern industry,the requirement for dynamic performance of the IMs drive systems is also increasing.Nevertheless,the design of the controller is still a challenging issue since the dynamic model of IMs is high order,non-linear and strong coupling.Hence,a lot of control methods have been proposed by scholars to achieve better performance of the IMs drive systems,such as backstepping control,sliding mode control,etc.However,most of these studies are based on asymptotically stable control law.Therefore,the finite-time tracking problem of IMs drive systems is not considered,which may limit IMs applications in practical engineering.Based on this,the finite-time control is adopted for enhancing the system convergence and disturbance-rejection ability.From the point of view of time optimization of the control system,the finite-time control is a time optimal control method.Besides of the advantages of excellent convergence performance,for the system with uncertain parameters and external disturbances,finite-time stabilization system can converge more quickly than other control technology,and also has better robustness and disturbance-rejection ability.Hence,it has important theoretical significance and industrial application value.Aiming at the problems existing in the traditional control method of IMs,this paper investigates a new control method for IMs based on the finite-time and command filtered backstepping theorem.The main research results are as follows:1.According to the mathematical model of IMs system,the position tracking control strategy of IMs is designed based on the backstepping method and combined with the finite-time and command filtering technology.By introducing the finite-time command filtering technique and using the first-order Levant differentiator,the problem of "explosion of complexity" is effectively avoided,and the derivative of virtual signal can be approximated in finite-time.Meanwhile,the novel error compensation mechanism has been proposed such that the error compensation system is finite-time stable.The new virtual control signals have been proposed such that the system can achieve desired tracking performance in finite-time.This method can not only hold the advantages of the conventional command-filtered backstepping control,but also guarantee the finite-time convergence.2.A mathematical model of IMs system considering input saturation is constructed.By using the fuzzy logic system to approximate the nonlinear term in the control system,and using the finite-time command filter to eliminate the influence of "explosion of complexity".A novel fuzzy finite-time command filtered backstepping approach is proposed by designing the new virtual control signals and the modified error compensation signals.Meanwhile,the adaptive technique estimates the unknown parameters of the controller.The designed control method can ensure that all of the closed-loop signals will be bounded in finite-time,and the tracking error of the system will converge to a sufficiently small neighborhood of the origin in finite-time.And the full consideration of input saturation makes the control method more practical.3.According to the simulation of Matlab/Simulink,command filtered backstepping control strategy is used to compare the simulation experiments.The results show that the controller proposed in this paper can not only holds the advantages of the compared one,but also achieve a better performance.