Filter- and Observer-Based Finite-Time Adaptive Fuzzy Control for Induction Motors Systems Considering Stochastic Disturbance and Load Variation

In this article, a finite-time adaptive fuzzy control scheme based on filter and reduced-order observer is proposed for induction motors (IMs) with load variation. First, the rotor position and the angular velocity of IMs are estimated by a reduced-order observer. Second, the unknown stochastic nonlinear functions are handled by the fuzzy logic systems. In addition, the finite-time control is combined with command filtering to solve the issue of explosion of complexity in the traditional backstepping method, and the errors compensation signal is introduced to reduce the filtering error, which can ensure the finite-time convergence and improve the robustness of the systems. The simulation and experimental results are given for validation of the proposed control strategy.

Automated summary

In this article, a finite-time adaptive fuzzy control scheme based on filter and reduced-order observer is proposed for induction motors (IMs) with load variation. The rotor position and the angular velocity of IMs are estimated by a reduced-order observer. The unknown stochastic nonlinear functions are handled by the fuzzy logic systems. The proposed control strategy combines finite-time control with command filtering and introduces errors compensation signal to improve the convergence and robustness of the systems. The simulation and experimental results validate the effectiveness of the proposed approach.