Application of new sliding mode control in vector control of PMSM

Abstract

Aiming at the characteristics of low observation accuracy and high chattering of traditional sliding mode observers (SMO), a new SMO is proposed to reduce chattering and improve accuracy. In PMSM vector control, PI control has the problems of poor anti-disturbance ability and speed pulsation, while the traditional sliding mode control (SMC) has the problem of serious chattering, Therefore, on this basis, an SMC based on the new reaching law is designed, and the simulation is carried out in Matlab/ Simulink. The simulation results show that the improved SMO has better performance and stronger stability than the traditional SMO. At the same time, compared with the traditional SMC and PI control, the SMC based on the new reaching law can make it respond well when the motor target speed changes suddenly, and effectively improve the problem of traditional SMC chattering, The control accuracy and steady-state error of the PMSM system are improved.

A cascaded linear active disturbance rejection control-based multi-stage model predictive control for permanent magnet synchronous motor

“…A PMSM control system with strong anti-interference ability and low parameter dependence is a performance indicator for achieving high-performance electric drive systems. At present, there are methods such as field oriented control (FOC) [8,9], model predictive control (MPC) [10,11,12,13], and direct torque control (DTC) [14,15,16,17] to achieve high-performance control of PMSMs. Among them, the MPC can replace vector control of the current inner loop, solving the problem of high parameter dependence.…”

Predictive current control method based on IPSO-ASMO for LIM

“…Sliding mode flux observer (SMO) based on the principle of sliding mode variable structure control is unaffected by external disturbances and has strong robustness to parameter variations in the system. Consequently, many experts and scholars have conducted in-depth research on this topic [11,12,13,14,15]. Reference [16] proposed a method based on error backpropagation neural network for optimizing the parameters of rotor position observer.…”

Research on sensorless control of PMSM based on novel double-sliding mode MRAS

“…The traditional PI control strategy has the problems of poor system stability and low control precision, which can't meet the requirements of PMSM high-performance control. At present, the research on PMSM control strategy mainly includes: neural network method [1,2,3,4]; Model reference adaptive method [5,6,7]; State observer [8,9,11]; High frequency injection signal method [12,13,14,15,16], etc [17,18,19]. However, the traditional MRAS has some problems, such as large parameter perturbation, slow reaction speed and poor tracking accuracy, which have triggered a large number of scholars at home and abroad.…”