Intelligent Complementary Sliding Mode Control For Six Phase Permanent Magnet Synchronous Motor

The control system of multiphase motor has the unique advantage to traditional three phase motor,such as low voltage and high power operation,small torque ripple,good fault tolerance and high reliability.It is widely useed in occasions of high requirements and limited conditions.For example,the traction system of high speed railway electric locomotive,the propulsion system of the ship power,the aircraft and aeronautics.In recent decades,many achievements have been made in the research of multiphase motor control system.In this paper,dual Y phase shift 30 degree six phase permanent magnet synchronous motor(PMSM)is chosen as the study object.Due to the system is influnced with uncertainty,such as parameter change and external disturbance,and with the phase fault situation of six phase PMSM.Complementary sliding mode control(CSMC)and intelligent complementary sliding mode control(ICSMC)are proposed to improve the dynamic performance of the system,enhance the robustness and achieve better control performance.Firstly,the definition,classification and structure of multiphase motor are introduced.The mathematical model of six phase PMSM is established in the natural coordinate system.The coordinate transformation relationship between static coordinate system and two phase rotating coordinate system is introduced.The mathematical model of six phase PMSM in double d-q coordinate system is obtained.The drive system is established by using the vector control strategy based on _di(28)0.Secondly,the CSMC method is designed to reduce the impact of uncertainties on the system and improve the dynamic performance of the system.The CSMC adopts the design with the combination of the generalized sliding surface and the complementary sliding surface.The saturation function is chosen as the switching function.Due to the uncertainty has important influence on the control performance of the system,and it can’t be measured by CSMC.The boundary layer thickness of the saturation function is obtained through experience and repeated experiments,which is very time consuming.In order to solve these problem,the ICSMC useing TSK fuzzy neural network as preestimator is designed based on CSMC.The TSK type fuzzy neural network is a five layer network structure using the Gauss function as membership function,which estimates the uncertainty of system online to improve system control performance and ensure stronger robustness in the six phase PMSM control system.Finally,the simulations of control system based on traditional PI control,CSMC and ICSMC are analyzed and contrasted.Meanwhile,this three control methods are applied to the fault-tolerant control system of six phase PMSM with phase fault.The results of simulation show that the proposed control methods are effective.No matter in normal operation of the system,or in the six phase PMSM phase failure.The ICSMC enables the system to have faster dynamic response,stronger robustness and better control performance than traditional PI control and CSMC.