Observer-based Fuzzy Adaptive Control Of Stochastic Systems For Asynchronous Motors

Induction motor has been widely concerned for its low cost,easy maintenance and reliable operation by industry,such as chemical and textile industry,electric vehicle industry,etc.However,in the industrial application,the induction motor system will be affected by the stochastic disturbances.The existence of stochastic disturbances will reduce the control performance of the system.In the control of induction motor,it is more practical to take the influence of stochastic disturbances into account.At the same time,in the design of traditional control methods,the controller design depends on the direct measurement of some state variables of the induction motor system,such as rotor position and rotor angular velocity.The acquisition of these state quantities requires the installation of mechanical sensors such as encoders,but the use of sensors will not only increases the hardware cost of the system,but also limits the application occasions,even increases the later maintenance and reduces the reliability of the system.Therefore,it is of great significance to design an effective position tracking control strategy for induction motor combined with the idea of sensorless control.Under the premise of considering stochastic disturbances,this paper combines backstepping control,fuzzy adaptive control,dynamic surface control technology and command filtering control technology to design the observer-based control strategy of induction motor stochastic system.The main research results are as follows: Firstly,under the premise of considering the stochastic disturbances,the controller is conducted for the induction motor drive system.Considering the high complexity,strong coupling and high order of the induction motor stochastic system,the fuzzy adaptive backstepping control scheme is applied to design the controller of the system.Then the quartic Lyapunov functions are selected to analyze the stability of the system according to the stochastic theory.Secondly,for the speed sensorless induction motor system,a reduced-order observer is constructed to estimate the rotor angular speed,which avoids the problems of high hardware cost and increased maintenance due to the use of speed sensor.The backstepping control method is used to design the controller of the system,combined with the dynamic surface control technology,the derivative of the virtual control function is directly obtained through the first-order low-pass filter,which avoids the problems of complex structure and large amount of calculation caused by repeated derivation.Thirdly,in view of the problem of the iron losses during the operation of induction motor,the fuzzy adaptive backstepping controller for induction motor stochastic system considering iron losses is designed.Furthermore,considering the influence of filter error,the command filter error compensation technology is applied to the controller design.While the command filter solves the "calculation explosion",the error compensation mechanism reduces the filter error and improves the control accuracy.Finally,in the MATLAB environment,the two control methods designed for the induction motor system are applied to the simulation experiment.The experimental results show that the proposed method can achieve effective position tracking control under the premise of considering the stochastic disturbances,and the designed observer can accurately estimate the rotor angular velocity signal.