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In practice, sensorless drive systems of interior permanent magnet synchronous motors (IPMSMs) are usually working in highly utilized conditions where fast changing uncertain loads, inverter losses, magnetic saturation, and other disturbance exist. These issues can reduce the performance and stability, which become the main vulnerability of sensorless drives. Linear extended state observer (LESO) or quadrature-phase-locked loop is conventionally adopted to estimate the speed and position. Without compensation or adaptive methods, fast changing uncertainties cannot be observed thoroughly. In this article, a third-order super-twisting extended state observer (STESO) is proposed to enhance the dynamic performance of position and speed estimation for IPMSM. Utilizing the high-order extended state and super-twisting algorithm, fast convergence and disturbance estimation can be achieved in STESO. The effectiveness and stability of STESO are analyzed and an optimized parameter selection method is presented. Comparative experimental results between the LESO and STESO verify the effectiveness and improvement of the proposed STESO against rapid speed and load variations.
Zhang et al. (Wed,) studied this question.