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Robust Model Predictive Speed Control of Induction Motors Using a Constrained Disturbance Observer

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  • Control Theory and Applications
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Abstract

This paper proposes an offset-free speed control method for induction motors using a model predictive control and disturbance observer. The proposed method has cascade control loops i.e. inner-loop model predictive torque control and outer-loop robust speed control. The outer-loop robust speed controller is composed of a stabilizing MPC and a discrete-time disturbance observer. The disturbance observer estimates the effects of the parameter uncertainties and the load torque to yield an offset free speed tracking, while taking the torque limit of the motor into account. This speed controller generates the reference torque for the inner-loop torque controller. A loss-minimizing continuous control set model predictive torque controller(CCS-MPTC) considering the current and voltage constraints of the motor is used as the inner-loop torque controller. Experimental results show a significant performance improvement when the torque constraints are considered in the DOB design.

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Authors and Affiliations

  1. Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, 01811, Korea

    Kooksun Lee & Jungjoo Lee

  2. Department of Electrical and Information Engineering and RCEIT, Seoul National University of Science and Technology, Seoul, 01811, Korea

    Young I. L. Lee

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  1. Kooksun Lee
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  2. Jungjoo Lee
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Correspondence to Young I. L. Lee.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Jong Min Lee under the direction of Editor-in-Chief Keum-Shik Hong. This work was supported by the grant from Seoul National University of Science and Technology (2019-0628).

Kooksun Lee received his B.S. and M.S. degrees in Electronics and Communications Engineering and Control and Instrumentation Engineering from Kwangwoon University, Seoul, Korea, in 2009 and 2011, respectively. He received his Ph.D. degree in Control and Instrumentation Engineering from Kwangwoon University. From 2016 to 2017, he was a postdoctoral researcher at Kwangwoon University and Seoul National University of Science and Technology, Seoul, Korea. Since 2018, he has been at Alienrobot Inc., Korea, where he is currently a chief technology officer. His research interests include nonlinear, robust control for electronic devices, alternative energy systems, and robotics.

Jeongju Lee was born in Korea in 1991. He received his B.S. and M.S. degrees in electrical and information engineering from Seoul National University of Science and Technology, Seoul, Korea, in 2016 and 2018, respectively. His research interests include electric machine drives and control engineering.

Young IL Lee received his B.S., M.S., and Ph.D. degrees in Control and Instrumentation Engineering from Seoul National University (SNU), in 1986, 1988, and 1994, respectively. He was visiting research fellow of Dept. of Engineering Science, Oxford University during 1998.2~1999.7 and 2007.2~2007.7. He worked in Gyeongsang National University from 1994 to 2001 and moved to Seoul National University of Science and Technology (SeoulTech) in 2001. He is currently a Professor of the Department of Electrical and Information Engineering of SeoulTech. He is a senior member of IEEE since 2015 and is serving as an editor of International Journal of Control, Automation and Systems (IJCAS) and International Journal of Automotive Technology (IJAT) from 2017 to 2019, respectively. Currently he is the director of electrical vehicle society of Korea Institute of Electrical Engineering (KIEE) and the head of research center of electrical and information technology of SeoulTech. His area of scientific interest includes MPC for systems with input constraints and model uncertainties, MPC method for DC-DC, AC-DC converter and DC-AC inverter, control of EV chargers, control of AC motors for EV application and energy management algorithm of micro-grids.

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Lee, K., Lee, J. & Lee, Y.I.L. Robust Model Predictive Speed Control of Induction Motors Using a Constrained Disturbance Observer. Int. J. Control Autom. Syst. 18, 1539–1549 (2020). https://doi.org/10.1007/s12555-019-0215-1

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  • DOI: https://doi.org/10.1007/s12555-019-0215-1

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