Model predictive sliding mode control of six-phase induction motor using nine-switch converter

Abstract

This article proposes a new control strategy to regulate the six-phase induction machine fed by a nine-switch converter. The traditional model predictive control method is a favorable feedback control routine in variable-drive applications. However, the lack of the term that assess the closed-loop stability in the conventional cost function formulation may cause potential closed-loop instability and be incapable of tolerating the parameter mismatch. Furthermore, the conventional model predictive control formulation cannot ensure global optimality in case of deviation from the nominal operating point. In this paper, the closed-loop stability is enhanced by including a sliding mode stability term in the objective function. The traditional cost function is redeveloped as a sliding mode control stability term, and the selection of the control input that satisfies the closed-loop loop stability condition is ensured. The robustness performance of the system is improved, and a better steady-state performance is achieved. The proposed control strategy is proved using a hardware setup including a six-phase 30 degrees spatially shifted induction motor and nine-switch converter prototype. The experimental results demonstrate that a secured six-phase induction motor operation is guaranteed while improving the closed-loop robustness.