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Adaptive fuzzy robust control of PMSM with smooth inverse based dead-zone compensation

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  • Control Theory and Applications
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Abstract

It is a challenging work to design high precision/high performance motion controller for permanent magnet synchronous motor (PMSM) due to some difficulties, such as varying operating conditions, parametric uncertainties and external disturbances. In order to improve tracking control performance of PMSM, this paper proposes an adaptive fuzzy robust control (AFRC) algorithm with smooth inverse based dead-zone compensation. Instead of nonsmooth dead-zone inverse which would cause the possible control signal chattering phenomenon, a new smooth dead-zone inverse is proposed for non-symmetric dead-zone compensation in PMSM system. AFRC controller is synthesized by combining backstepping technique and small gain theorem. Discontinuous projectionbased parameter adaptive law is used to estimate unknown system parameters. The Takagi-Sugeno fuzzy logic systems are employed to approximate the unstructured dynamics. Robust control law ensures the robustness of closed loop control system. The proposed AFRC algorithm with smooth inverse based dead-zone compensation is verified on a practical PMSM control system. The comparative experimental results indicate that the smooth inverse for non-symmetric dead-zone nonlinearity can effectively avoid the chattering phenomenon which would be caused by nonsmooth dead-zone inverse, and the proposed control strategy can improve the PMSM output tracking performance.

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Xingjian Wang & Shaoping Wang

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  1. Xingjian Wang
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  2. Shaoping Wang
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Correspondence to Xingjian Wang.

Additional information

Recommended by Associate Editor Sung Jin Yoo under the direction of Editor Euntai Kim. This work was supported by the National Natural Science Foundation of China under Grant No. 51305011, National Basic Research Program of China (973 Program) under Grant No. 2014CB046402 and the Fundamental Research Funds for the Central Universities under Grant No. YWF-14-FGC-016, YWF-13-T-RSC-064.

Xingjian Wang received the Ph.D. and B.Eng. degrees in mechatronics engineering from Beihang University, China, in 2012 and 2006. From 2009 to 2010, he was a visiting scholar in the School of Mechanical Engineering, Purdue University, West Lafayette, IN, U.S.. He is currently with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests include adaptive and nonlinear control, fault diagnostic, prognostic and health management, active fault tolerant control.

Shaoping Wang received the Ph.D., M.Eng. and B.Eng. degrees in mechatronics engineering from Beihang University, China, in 1994, 1991 and 1988. She has been with the Automation Science and Electrical Engineering at Beihang University since 1994 and promoted to the rank of professor in 2000. She was honoured as a "Changjiang Scholar Professor" by the Ministry of Education of China in 2013. Her research interests include engineering reliability, fault diagnostic, prognostic and health management, active fault tolerant control.

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Wang, X., Wang, S. Adaptive fuzzy robust control of PMSM with smooth inverse based dead-zone compensation. Int. J. Control Autom. Syst. 14, 378–388 (2016). https://doi.org/10.1007/s12555-015-0010-6

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  • DOI: https://doi.org/10.1007/s12555-015-0010-6

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