Ultralocal Model Based Model Predictive Torque Control of Induction Motor Drives With Model Free Speed Controller

Yanqing Zhang, Liang Shao, Zhonggang Yin, Cong Bai, Jing Liu

Abstract: To enhance the robustness of model predictive torque control (MPTC) drive systems, an ultralocal model (ULM) based model predictive torque control with model free control (ULM-MPTC-MFC) is proposed in this article. First, a typical MPTC is established based on the conventional induction motor (IM) model, which is sensitive to the motor parameters variation. It is known that the performance will degrade substantially once the parameters mismatch occur. To address this issue, an ULM is constructed, in which the ULM is utilized to not only predict stator current, but also predict stator flux. During the prediction process, the parameters mismatch can be eliminated accordingly since the input and output of the system are the only two items used in ULM. Moreover, to further improve the robustness of the system, the model free control (MFC) is introduced to replace the conventional PI control in the speed loop. By considering the MFC theory, an independent ULM sliding mode controller is established. The Lyapunov stability theory is used to prove the stability of the proposed method. Compared with the conventional MPTC, experimental results show that the proposed ULM-MPTC-MFC has the better robustness against motor parameters variation and step load change.

External IDs:dblp:journals/tie/ZhangSYBL25