Adaptive fuzzy control with minimal leaning parameters for electric induction motors
In this paper, an effective adaptive tracking control approach is constructed for the sixth-order induction motor model which is in discrete-time form. The fuzzy logic systems (FLSs) are applied to estimate a control law and used to a block strict feedback form (BSFF) which is in existence of bounded disturbances. Then, a desired optimal control can be achieved. Depend on the Lyapunov analysis approach, for the considered system, the stability is guaranteed, the tracking error can be ensured to a small neighborhood around zero, and the weight estimates can be insured to semi-global uniformly ultimately bounded (SGUUB). An advantage for the controlled system is that the proposed algorithm needs only less parameters which is different from the existing results, therefore, it can reduce the calculation amount. The practicality of the scheme is verified via a simulation.
the fuzzy logic systems (flss) adaptive control the motor model the stability analysis