Novel Adaptive Model-Free Speed Control for Uncertain Permanent Magnet Synchronous Motor

The problem is that permanent magnet synchronous motor model parameters are difficult to determine accurately or may be distorted during operation. This results in a significant reduction in controller performance. Therefore, it is necessary to use algorithms to compensate for parameter deviations, such as observers and parameter adaptation. This paper aims to build a current controller of a permanent magnet synchronous motor that does not require any motor model information. At the same time, to ensure the Maximum torque per ampere (MTPA) condition, the d-axis current must also be controlled stably at zero. Based on the above reasons, a novel Adaptive Back-Stepping Current Controller (ABS-CC) - based field-oriented control scheme for a permanent magnet synchronous motor is investigated in this paper. Specifically, ABS-CC control law is utilized to generate the control signal based on the mathematical model and neuron network, which guides the motor toward the given current reference. Finally, a simulation experiment is carried out to validate the theoretical conclusions, which show the high performance of the designed current control scheme.