Research on improvement of PMSM speed sliding mode observer with time-varying parameters
To address the decreasing accuracy and performance of the traditional speed sliding mode observer for Permanent Magnet Synchronous Motors (PMSM) caused by variations in motor parameters,this paper proposes an enhanced sliding mode observer,which integrates parameter identification with the sliding mode observer.During the operation of the speed sliding mode observer,the stator resistance,inductance,and rotor flux linkage are identified in real-time by employing the Particle Swarm Optimization (PSO) algorithm,and the motor parameters within the sliding mode observer are optimized based on the identified values.Furthermore,improvements are made to address the performance degradation of the PSO algorithm in high-dimensional problems,aiming to enhance its identification accuracy and efficiency.Our simulation and experimental validations demonstrate the enhanced sliding mode observer,integrated with parameter identification,exhibits a greater robustness against parameter variations and disturbances during motor operation with a higher identification accuracy.