Optimization-Based Sensorless Control of Permanent Magnet Synchronous Motor Drives with Modified Newton Method

This paper proposes an optimization-based sensorless control method for interior permanent magnet synchronous motors (IPMSMs) by introducing an improved Newton algorithm with line search for rotor position estimation. The proposed method incorporates line search strategies with classical Newton algorithm to improve convergence behavior and robustness. Three line search techniques are investigated: uniform line search, golden section search, and derivative-based bisection. The simulation results demonstrate that the proposed method achieves faster convergence with fewer iterations and exhibits a modest improvement in the convergence region under varying initial conditions. The results confirm that proposed method offers superior reliability compared to the conventional approach, particularly in scenarios with large initial estimation errors or non-ideal system conditions.