Adaptive NN Finite-Time Tracking Control for PMSM with Full State Constraints

This paper proposes a finite-time adaptive tracking control scheme for permanent magnet synchronous motors (PMSM) with full state constraints. In order to deal with full state constraints, the nonlinear transformation function is first introduced to transform the constraint problem into a non-constraint problem. Then, we will provide a tracking differentiator that get the differentiation of the virtual control laws. At the same time, the neural networks (NN) are employed to approximate unknown nonlinearities. Finally, simulation results are given to validate the proposed control scheme.