A New State Estimator of PMSM Using Adaptive Extended Kalman Filter

Abstract:

This paper presents a new permanent magnet synchronous motor (PMSM) drive technique using adaptive state estimator for high-performance motion control to estimate the instantaneous speed, position and disturbance load torque. In the proposed algorithm, the model reference adaptive control (MRAC) method is incorporated to identify the variations of inertia moment, and the identified inertia is used to adapt the extended Kalman filter (EKF), which is an optimal state estimator to provide good estimation performance for the rotor speed, rotor position and disturbance torque with low precision quadrature encoder in a random noisy environment. In addition, the disturbance–rejection ability and the robustness to variations of the mechanical parameters are discussed and it is verified that the system is robust to the modeling error and system noise. Simulation and experimental results confirm the validity of the proposed estimation technique.

• Periodical: Advanced Materials Research (Volumes 430-432)
• Pages: 772-780
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.430-432.772
• Online since: January 2012
• Authors: Xin Zhong Ding, Cheng Rui Zhang, Le Hua Yu, Hu Xiu Li
• Keywords: Extended Kalman Flter (EKF), Model Reference Adaptive Control, Motion Control, Parameter Identification, State Estimator

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