Parameter Identification-based PMSM Complex Sliding Mode Control Strategy Without Position Sensor

Permanent Magnet Synchronous Machine(PMSM)is widely used in transportation,aerospace and other fields because of its high efficiency and energy saving,high power density and reliable operation.The conventional control system can no longer meet the current demand of motor control accuracy,and the continuous improvement of motor system control accuracy is the need of modern technology development.In the traditional control strategy,PI control is vulnerable to the interference of motor parameter variations and external disturbances,and the installation of mechanical sensors to obtain the rotor position signal both increases the cost of the motor and affects the control performance of the motor.To deal with the above problems,this paper combines model-referenced adaptive theory and sliding mode control to investigate the PMSM parameter variation,controller and rotor position observer,respectively,in order to improve the control accuracy of the motor in variable operating conditions environment.The research in this article is as follows:(1)The current research status of motor parameter identification and position sensorless control technology is discussed.The identification method of motor parameters,three control strategies of motor and position sensorless control technology are elaborated;the mathematical model of PMSM in different coordinate systems is derived and SVPWM technology and its implementation process are introduced.The online identification of motor parameters,vector control strategy and sliding mode control technology are taken as the research contents of this paper.(2)Set up the online identification system of PMSM parameters.The influencing factors of motor stator inductance,stator resistance,magnetic chain,and the influence of parameter changes on current loop,speed loop and observer are analyzed.An adaptive law with filtering correction coefficients is proposed,and then a model reference adaptive identification system is designed to identify the motor parameters online in the normal state;finally,the PMSM parameter mismatch is simulated to verify the effectiveness of the improved algorithm on the variable parameters of the motor.(3)Design the PMSM position sensor-less composite sliding mode control system.At first,we analyze the reasons of jitter vibration and its effects in the sliding mode control system,and propose a new sliding mode controller with variable exponential convergence law for the shortcomings of PI and common sliding mode control,and simulate and verify the robustness of the convergence law.Next,based on the superhelix algorithm,a global integral second-order sliding mode observer is designed to solve the problem of low observation accuracy of firstorder sliding mode observer.Finally,a new switching function is built to effectively reduce the jitter and vibration caused by the switching process.(4)Modeling and analyzing the composite sliding mode control system and parameter online compensation system.The mathematical model of the complex control system is derived,and the fuzzy algorithm is adopted to realize the online adaptive adjustment of the three gain parameters of the observer,which comes with filtering effect,and finally the quadrature phaselocked loop is used to estimate the rotor position signal and speed of the motor.Since the parameters in the composite control system are all given values,the motor parameter values are identified online and updated to the control system in real time to improve the dynamic performance and control accuracy of the control system.The feasibility of the proposed theory is verified by modeling simulation.(5)Experimental verification of the complex sliding mode control algorithm.Build the PMSM physical platform,design the control system hardware and software,compare the traditional control system,and verify the superiority of the composite algorithm through experimental results.