Intelligent Sliding Mode Chaos Control Of Disturbed Permanent Magnet Synchronous Motor

Permanent Magnet Synchronous Motor(PMSM)is widely used in electric vehicles,electric power production,aerospace and medical equipment because of its simple structure,high output power,high power density,small size and low failure rate.However,PMSM itself is a strongly coupled,nonlinear and dynamic time-varying system,which leads to complex nonlinear dynamic behavior under some specific system parameters.For example,when the parameters of the motor system are affected by operating temperature,flux,current and other factors to the critical point of chaotic behavior,the motor begins to appear chaotic behavior.The chaotic behavior not only affects the stability and performance of the electric drive system,but also damages the controller components.Therefore,in order to make the drive system stable,the chaotic behavior of PMSM must be effectively controlled.In addition,the motor system may have parameter uncertainty due to mechanical loss,insufficient measurement accuracy and other reasons.Therefore,this paper takes PMSM with disturbance input and parameter uncertainty as the research object,and carries out related research on chaotic nonlinear control method based on sliding mode variable structure control theory.The main research contents and results of this paper are as follows :(1)The dynamic mathematical model of PMSM is derived.Based on nonlinear dynamic analysis methods such as bifurcation diagram,Lyapunov exponent,phase trajectory and Poincare section,the numerical characteristics of PMSM chaotic behavior are studied.It is proved that PMSM is highly sensitive to small changes in initial conditions.When the system parameters change to a specific range,chaos will occur in the motor system.(2)Aiming at the problem of PMSM chaotic control with uncertain parameters.Firstly,the T-S fuzzy model of permanent magnet synchronous motor with uncertain parameters is given based on Takagi-Sugen(T-S)fuzzy model theory.Next,the proposed T-S fuzzy model is analyzed by using Lyapunov stability theory and linear matrix inequality(Linear Matrix Inequality,LMI)method,and the problems related to controller design are solved.Finally,the sliding mode controller is designed by using virtual feedback and sliding mode control method.Through simulation,the control effect of this controller is compared with that of the traditional parallel distributed compensation controller(PDC)applied to T-S model,which proves the superiority of this controller.(3)In order to control the chaos phenomenon of PMSM and reduce the chattering phenomenon in the controller,a fuzzy sliding mode control strategy is designed based on fuzzy control theory and sliding mode control theory.The fuzzy control is used to adjust the switching term of the controller,and the sliding mode control is used to overcome the external interference of the system,which fully combines the advantages of the two.The simulation results show that the control strategy not only reduces the chattering phenomenon of the controller,but also quickly suppresses the chaotic phenomenon of PMSM,and has certain robustness.(4)Whether the appropriate control parameters can be selected is very important for the sliding mode controller to exert its excellent performance.In order to better solve the problem of sliding mode control parameter selection,firstly,the principle and characteristics of particle swarm optimization algorithm(PSO)are deeply studied.Then,aiming at the optimization problem existing in PSO optimization algorithm,an improved PSO optimization algorithm is proposed.Then,four algorithm optimization test functions are used to evaluate and compare the hybrid particle swarm optimization algorithm and the other two commonly used particle swarm optimization algorithms,so as to verify the advantages and feasibility of the algorithm designed in this paper.Finally,the algorithm is used to optimize the parameters in the fuzzy sliding mode controller proposed in this paper to obtain the optimal controller parameters and realize the optimization of the fuzzy sliding mode controller.The simulation results show that the controller has better control quality after optimization.