Barrier Lyapunov function-based adaptive fuzzy control for induction motors with iron losses and full state constraints

This paper is concerned with the problem of adaptive fuzzy control for induction motors (IMs) with iron losses and full state constraints based on the barrier Lyapunov function method. The state variables are constrained by the inherent properties of the IMs, and the barrier Lyapunov function (BLF) is introduced to guarantee that the full state constraints are not violated. In addition, fuzzy logic systems are utilized to approximate the nonlinearities. It is proved that all the signals of closed-loop system are guaranteed to be bounded and the tracking error converges to the neighborhood of the origin asymptotically. Finally, simulation results show the effectiveness of the proposed scheme.