Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control

To enhance the position estimation accuracy of permanent magnet synchronous motor (PMSM) speed-sensorless control, a simplified hybrid adaptive kalman filter (SHAKF) with fading-triggered resonance (FTR) is proposed in this brief. By simplifying the iterative calculation of forgetting factor and noise covariance matrix, the computational burden is effectively reduced. Through the FTR mechanism, the steady-state error compensation without compromising stability is achieved. The stability and convergence are rigorously analyzed. Finally, the experimental results validate the superiority of the proposed sensorless control strategy in steady-state accuracy, dynamic speed response, and computational efficiency.