Neuro‐adaptive finite‐time optimal tracking control for permanent magnet synchronous motors with full‐state constraints

Summary In this article, the optimal tracking control problem is investigated for permanent magnet synchronous motors (PMSMs) with full‐state constraints. By constructing multiple barrier‐type performance index functions, a neuro‐adaptive finite‐time optimized control scheme is presented under identifier‐actor‐critic architecture, where the virtual control laws and the actual laws are designed to optimize corresponding subsystems. It is proven that all signals of the closed‐loop system are uniformly ultimately bounded under the proposed control strategy, and the position tracking error converges to a small neighborhood of the origin in finite time. Besides, the system states are constrained to the effective operation range all the time. Finally, the simulation results and comparisons are carried out to further demonstrate the effectiveness of the proposed optimal control approach.