Control of Permanent Magnet Synchronous Motors Based on Least Squares Method

Luenberger observers exhibit superior dynamic performance, enhanced parameter robustness, and elevated system stability. However, when the operating conditions and external environmental factors of permanent magnet synchronous motors (PMSMs) vary, parameter mismatches inevitably arise in sensorless control strategies relying on fundamental wave models. This paper proposes a hybrid parameter identification method integrating Luenberger observers with a recursive least squares (RLS) algorithm incorporating a forgetting factor, enabling real-time identification of stator resistance and inductance parameters. This approach effectively suppresses rotor position estimation errors induce d by PMSM parameter deviations.