Dual-mode predictive control of a rotor suspension system

Science China Information Sciences volume 63, Article number: 112204 (2020) Cite this article

Abstract

Rotor active magnetic bearing (rotor-AMB) systems are frequently used to alleviate vibrations for various applications such as in national defense, manufacturing industries, IC production, and aerospace engineering. One obstacle to improve machining efficiency and quality is the open-loop instability of rotor-AMB systems during the machining process. We built a closed-loop processing platform using a spindle rotor installed with AMBs and thereby developed a rotor-AMB suspension system embedded with a dual-mode predictive controller (DMPC). The performance of the system is thus substantially improved. In the proposed DMPC, both model-based prediction and receding horizon optimization are utilized to guarantee the closed-loop stability of the rotor-AMB suspension systems with input constraints. Finally, the effectiveness and superiority of the proposed method are examined through substantial levitation experiments on a machining platform with installed AMBs.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. U1713203, 61803168, 51729501) and China Postdoctoral Science Foundation (Grant No. 2018M642822).

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Affiliations

  1. Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Yue Wu, Gui-Ping Ren & Hai-Tao Zhang

  2. State Key Laboratory of Digital Manufacturing Equipments and Technology, Wuhan, 430074, China

    Yue Wu, Gui-Ping Ren & Hai-Tao Zhang

Authors
  1. Yue Wu
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  2. Gui-Ping Ren
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  3. Hai-Tao Zhang
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Corresponding author

Correspondence to Hai-Tao Zhang.

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Cite this article

Wu, Y., Ren, GP. & Zhang, HT. Dual-mode predictive control of a rotor suspension system. Sci. China Inf. Sci. 63, 112204 (2020). https://doi.org/10.1007/s11432-019-9896-2

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Keywords

  • dual-mode predictive control
  • system identification
  • optimization control
  • model predictive control
  • suspension control