Finite-time Fuzzy Adaptive Control Of Permanent Magnet Synchronous Motor Stochastic Syste

The permanent magnet synchronous motors(PMSMs)are widely used in various fields because of their advantages of easy use,low energy consumption,small volume and long service life.Nevertheless,the system of PMSMs are multivariable and highly nonlinear,and is susceptible to external load disturbance,motor parameter change and other uncertain factors in practical application.For the sake of better realize the position tracking control of PMSM,Effective control strategies need to be studied.For the sake of solve the control problem of PMSMs,the relevant control strategies are applied to PMSMs,such as sensorless control,backstepping control,robust control,intelligent control and sliding control etc.Nevertheless,the above methods do not take into account the actual operation,PMSMs will produce stochastic interference due to the changes of motor torque,selfinductance and other related parameters caused by damping torque and magnetic saturation.The design accuracy of the controller and the stability of the control system will be reduced due to the stochastic disturbance.In a great deal of practical systems,input saturation is a common problem,when there is an input constraint problem in the motor,the over-voltage will damage the motor and seriously affect the normal use of PMSMs.In addition,PMSMs will produce iron loss due to no-load or light load in actual use,which will reduce the stability of PMSMs to a certain extent.Therefore,it is necessary to consider the input constraints,iron losses and stochastic interference of PMSMs in actual operation.The following are the main research results of this paper:(1)The position tracking control problem of a stochastic nonlinear systems is studied,a finite-time command filtering control method is proposed.Firstly,this paper considers the stochastic interference of permanent magnet synchronous motor in actual operation,which is more in line with the actual operation.Then,the finite-time control(FTC)technology is introduced into the stochastic nonlinear system to improve the control accuracy,faster response speed and stronger anti-interference ability of the system.Last but not least,the constancy of SNSs is testified.(2)Aiming at the position tracking control problem of PMSMs stochastic nonlinear systems with input constraints and load disturbances,a finite-time adaptive fuzzy dynamic surface control(DSC)method is proposed.Firstly,DSC technology is used to avoid the problem of "calculation explosion" in backstepping design.Secondly,the FTC is applied to the stochastic nonlinear system of permanent magnet synchronous motors.Last but not least,the constancy of SNSs is testified.The simulation results testify that the control technology proposed in this chapter has faster response speed and higher control accuracy.(3)Aiming at the problems of stochastic interference and iron losses in position tracking of PMSMs,a finite-time fuzzy command filter control(CFC)strategy is proposed.Firstly,the issue of "computational complexity" in backstepping control is solved by using CFC strategy,and the introduced compensation signal can eliminate the filtering error.Then,the combination of CFC technology and FTC technology is applied to PMSMs stochastic nonlinear system.Through MATLAB comparative simulation,CFC method is compared with DSC method.The simulation comparison diagram indicates that CFC method has faster convergence speed and when the external load torque changes,it can quickly respond and accurately track the reference signal.