Intelligent Fractional-order Backstepping Control Of Permanent Magnet Linear Synchronous Motor

Since the modernization of industry,the development of industrial core technology tends to be precise,high-speed and intelligent.The linear motor has a wide speed range,relatively simple structure,better smooth motion performance,lower noise,and higher repeat positioning accuracy because it takes away the intermediate link of the traditional rotary motor.Its higher acceleration makes the response time of the system much shorter,and the corresponding control performance is also better than that of traditional rotating motors.Permanent magnet linear synchronous motors（PMLSM）have been commonly used in finishing robots,transportation ships,aerospace,microelectronics and other industrial fields.However,PMLSM is susceptible to uncertainties,such as parameter changes and load disturbances,so the system does not operate well and its tracking accuracy deteriorates.In order to improve the control performance and tracking accuracy of the system,so that the robustness of the system can also be enhanced,and to address the influence of uncertainty factors in PMLSM,this thesis conducts an intelligent fractional-order backstepping control study for permanent magnet linear synchronous motors.First,this thesis describes the basic structure and working principle of PMLSM,and builds a mathematical model of PMLSM including uncertainty factors.The basic principle of PMLSM magnetic field directional vector control is described,and the vector control system of PMLSM is built.The causes of uncertainties within the system and the impact on the system performance are analyzed.Next,a brief introduction to the backstepping control theory is given,followed by the derivation of the dynamic equations of the PMLSM servo system,based on which the backstepping controller is designed.For the problems of low accuracy of traditional backstepping control position tracking and susceptibility to uncertainty factors,this thesis proposes a fractional-order backstepping control scheme.The purpose of adding fractional order calculus in traditional backstepping control is to increase the degrees of freedom of the controllable parameters to make the system response faster and the control performance of the system stronger as a way to reduce the steady-state error of the system and strengthen its robust performance.In order to verify the feasibility of the proposed scheme,simulations were carried out,and from the simulation results,it can be seen that the scheme is feasible and better than the conventional backstepping control.Finally,to make the robust performance and tracking performance of PMLSM servo system further enhanced,for the problem of uncertainty factors in the system,this thesis proposes to use a combination of fractional-order backstepping control and intelligent methods applied to the position tracking of PMLSM.A function-linked fuzzy neural network is used as an observer of the uncertainty term of the system,and a compensator is used to compensate for the observation error caused by insufficient neurons in the neural network and to compensate for the extraneous disturbances instantaneously during the control process to further improve the tracking performance and robustness of the fractional-order backstepping control system.From the simulation results,it can be seen that the intelligent fractional-order backstepping control further improves the tracking performance and robustness of the system compared with the fractional-order backstepping control.