A State Detection Method of Induction Motor Based on PSO-BS-SMO

In order to improve the performance of sliding mode observer in detecting the state of induction motor, a state detection method based on particle swarm optimization (PSO)-backstepping (BS)-sliding mode observer (SMO) is proposed in this paper. In this method, the controller is constructed and the parameters of the control rate are optimized, so that the tracking accuracy and robustness of the new observer are improved relative to conventional observer, exponential observer, PI and PID. Firstly, the state equation of the induction motor under stator and rotor winding fault and stator current sensor fault is established. Secondly, the new sliding mode observer is designed using the backstepping method based on the new reaching law. Then, the new fitness function and PSO is used to optimize the parameters of the new sliding mode observer. Finally, the simulation comparison experiment of stator current state detection is carried out under the simulated fault condition of induction motor. The feasibility of the method is verified by comparing the state tracking situation and the state detection error. The comparative experimental results show that the method has less jitter, stronger robustness, and higher state tracking accuracy when detecting stator current states under different faults.