Stability and Convergence Analysis of Reduced-Order Observer With Alternating Parameter Adaptation for Sensorless Variable Flux Reluctance Motor Drives

Direct current excited variable flux reluctance motors (DC-VFRMs) consist of only copper windings and iron cores. With the further adoption of sensorless control, these motors have great potential in low-cost and high-reliability applications. However, due to factors such as temperature and magnetic saturation, stator resistance and mutual inductance may change, leading to increased observer errors or even system instability. Traditional observer-based parameter adaptation methods typically focus on identifying a single parameter, which limits their effectiveness when multiple parameters vary simultaneously. To address these issues, an improved reduced-order observer (RO) with parameter adaptation is proposed, which is supported by small-signal modeling and stability analysis. Secondly, two equilibrium points are constructed by injecting trapezoidal-wave field current signals to alternately identify stator resistance and mutual inductance. Then, a numerical iterative method is proposed to demonstrate the convergence of the proposed method. The convergence conditions are derived through theoretical analysis. Finally, comparative experiments are conducted on the 12/10 DC-VFRM platform, and the results show that the estimation errors of stator resistance, mutual inductance, position, and torque are effectively suppressed.