Model-Free Predictive Control Based on the Integral Sliding Mode Observer for Induction Motor

Abstract

The model-free predictive control (MFPC) is a new trend in the studies of the predictive control theory. In the MFPC, the classic model of the plant is substituted by an ultra-local model (ULM) that does not depend on the parameters and the uncertain variables of the system. In this manner, the model-free scheme improves the robustness of the predictive control system. This paper presents an integral sliding mode observer (ISMO)based MFPC for the induction motor (IM) drive. The proposed ISMO is utilized to establish an ULM for the IM. The ISMO guarantees the complete robustness of the system throughout an entire period. This feature is studied by using the Lyapunov candidate function. The implementation of the proposed MFPC is performed by the finite-set predictive current control (FSPCC). The proposed ISMO-based MFPC is evaluated through simulations and experimental tests.