Robustness Improvement of FCS-MPTC for Induction Machine Drives Using Disturbance Feedforward Compensation Technique

Finite control set-model predictive torque control (FCS-MPTC) has a fast dynamic response because this algorithm directly selects the optimal voltage vector by its cost function for induction machine drives fed by voltage source inverter (VSI). However, belonging to open-loop control paradigm, the F...

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Bibliographic Details
Published inIEEE transactions on power electronics Vol. 34; no. 3; pp. 2874 - 2886
Main Authors Yan, Liming, Dou, Manfeng, Hua, Zhiguang, Zhang, Haitao, Yang, Jianwei
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Finite control set-model predictive torque control (FCS-MPTC) has a fast dynamic response because this algorithm directly selects the optimal voltage vector by its cost function for induction machine drives fed by voltage source inverter (VSI). However, belonging to open-loop control paradigm, the FCS-MPTC has torque tracking error due to inevitable load disturbance and mismatched model parameters in reality. In traditional FCS-MPTC, the outer loop, i.e., speed loop, adopts a classic proportional integral (PI) controller, abbreviated as PI-MPTC. The lumped disturbance is only suppressed by a PI controller. However, pole placement of the PI controller is usually designed by cut-and-trial, which is difficult to simultaneously achieve optimal dynamic performance and optimal suppression of lumped disturbance. In this paper, the FCS-MPTC with mismatched parameters is first analyzed. Second, the deficiencies of the traditional PI controller are introduced. Third, disturbance feedforward compensation-based-model predictive torque control (DFCB-MPTC) of induction machine is proposed to compensate lumped disturbance and improve the performance of the system. Furthermore, a simplified stator flux observer is proposed, whose gain matrix is independent of rotor speed. Experimental results verify the feasibility of the proposed DFCB-MPTC. Compared with traditional PI-MPTC, the proposed DFCB-MPTC has better dynamic performance, steady performance, and stronger robustness.
ISSN:0885-8993
1941-0107
DOI:10.1109/TPEL.2018.2842743