Adaptive SDRE-Based Nonlinear Sensorless Speed Control for PMSM Drives

This paper presents a new adaptive nonlinear control approach for permanent magnet synchronous motor (PMSM) drives, without requiring speed sensors. The proposed approach is based on state-dependent Riccati equation (SDRE) control technique and its real-time computation method by gradient-type neural networks, that allows one to control PMSM online. For this purpose, the unknown parameters of the PMSM drive; stator resistance, load torque, and motor speed, are also estimated using an extended Kalman filter (EKF) algorithm. The resulted adaptive algorithm is independent from any initial conditions, relatively fast to achieve nonlinear system speed tracking control, numerically not complex, and easily applicable to real-time control of PMSM drives. This new adaptive approach for sensorless control of PMSM drives is demonstrated through an illustrative simulation for the proof of concept.