Super-twisting algorithm based sliding-mode observer with online parameter estimation for sensorless control of permanent magnet synchronous machine

Online parameter estimation could improve the performance of sensorless control. In this paper, a super-twisting algorithm (STA) based second-order sliding-mode observer (SMO) sensorless control with online stator resistance estimation is proposed. The chattering problem and time delay, which could not be avoided in conventional SMO, are eliminated in this STA based second-order SMO. At the same time, a parallel online stator resistance estimation algorithm is proposed based on a first-order SMO. With the help of the online stator resistance estimator, the performance of the sensorless control is improved in terms of system stability and position accuracy. The stability of the online stator resistance estimator is proved by Lyapunov function. Finally, the STA based sensorless control method with online stator resistance estimation is verified and compared with conventional methods by simulation and experiments.