A Robust Vector Control of Permanent Magnet Synchronous Machines Resilient to Parameter Uncertainty

Accurate flux estimation is important for high-performance control of the Permanent Magnet Synchronous Machines (PMSMs). Parameter uncertainty reduces this accuracy and degrades the controller’s performance. This paper presents a vector control of PMSMs which utilizes a combination of the flux estimation based on current and voltage models of PMSMs via a weighting factor to ensure the best performance at all speeds for excitation at dominant frequencies. The weighting factor can be chosen so that the controller can effectively act as a flux regulator or a current regulator. Furthermore, this paper introduces a framework to formulate the system dynamics suitable for robust analysis and determine the Worst Case Gain (WCG) of the reference tracking transfer function of the closed loop system. The weighting factor is optimized in order to minimize the WCG in presence of parameter uncertainty for inductances and resistance. Using this analysis, the proposed regulator can benefit from the optimal blending of the two flux estimation methods and is robust to parameter uncertainty compared to conventional current and flux regulators.