4.6 Article

Integral Super Twisting Sliding Mode Based Sensorless Predictive Torque Control of Induction Motor

期刊

IEEE ACCESS
卷 8, 期 -, 页码 186740-186755

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3028845

关键词

Torque; Rotors; Torque control; Observers; Robustness; Mathematical model; Stators; Direct torque control (DTC); induction motor (IM); model predictive torque control (MPTC); sliding mode control (SMC); sliding mode observer (SMO); super twisting control (STC)

资金

  1. Basic Science Research Program through the National Research Foundation of Korea - Ministry of Education [2016R1D1A1B01008058]
  2. Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) - Korea government Ministry of Trade, Industry and Energy [20204030200090]

向作者/读者索取更多资源

In the direct torque control (DTC) of induction motor (IM) drive systems utilizing model predictive torque control (MPTC) in the inner loop and classical proportional integral (PI) control in the outer loop is prone to weaknesses, such as uncertainties, external disturbances, parameter variations, and nonlinear dynamics. A high-performance control system for speed and torque is required to guarantee a smooth and robust control architecture that can withstand such unpredictable effects. In this study, we propose an integral super twisting sliding mode control (ISTSMC) to address the shortcomings of the classical PI used in the outer loop of DTC drive systems. A sliding mode speed observer is also designed and utilized to overcome problems associated with mechanical sensors. The robustness of the proposed control strategy and fast dynamic speed response are compared favorably with a benchmark PI controller and conventional sliding mode control (SMC). The ability of the proposed system to regulate both speed and torque was evaluated through simulations, under various fault perturbations, parameter variations, and load disturbances, conducted in MATLAB/ Simulink. Various performance indices were used to demonstrate the superior performance of the proposed strategy compared to a benchmark PI system and conventional SMC-based MPTC approaches.

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