A Composite Control Method for Permanent Magnet Synchronous Motor System with Nonlinearly Parameterized-Uncertainties

In many industrial practices, it needs a permanent magnet synchronous motor to provide enough torque, such as autonomous vehicle driving. In the operation of a permanent magnet synchronous motor, the nonlinearly parameterized-uncertainties degrade control performances, causing the instability of motor speed and output torques. Based on the analysis of temperature effects and friction torque model, a composite controller is proposed in this paper which considers model uncertainties and external disturbances. An adaptive controller involving an online time-varying scaling gain is employed to eliminate the influence of nonlinearly parameterized-uncertainties. In addition, an extended state observer (ESO) is used to estimate the disturbance in the control system in which the estimated value is used to compensate for the feed-forward. Numerical simulation and experiment are performed and the results show that the proposed method may alleviate the performance degradation due to nonlinearly parameterized-uncertainties and disturbances. Simultaneously, it may improve the stability and anti-disturbance capacities of the system.