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Controller design for fractional-order interconnected systems with unmodeled dynamics

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Abstract

This paper focuses on the output feedback tracking control for fractional-order interconnected systems with unmodeled dynamics. The reduced order high gain K-filters are designed to construct the estimation of the unavailable system state. Unmodeled dynamics is extended to the general fractional-order dynamical systems for the first time which is characterized by introducing a dynamical signal r(t). An adaptive output feedback controller is established using the fractional-order Lyapunov methods and proposed by novel dynamic surface control strategy. Then, it is confirmed that the considered system is semi-globally bounded stable and the errors between outputs and the desired trajectories can concentrate to a small neighborhood of the origin. Finally, a simulation example is introduced to demonstrate the correctness of the supplied controller.

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Acknowledgements

The authors would like to thank the Associate Editor and the anonymous reviewers for their keen and insightful comments which greatly improved the contents and the presentation of this article significantly. The work described in this paper was fully supported by National Defense Basic Scientific Research Project (Project No. JCKY2019407D001), National Key R&D Program of China (2018YFB1308300), National Natural Science Foundation of China (61933009, 61751309, 618255304, U20A201186), Natural Science Foundation of Hebei Province (F2020203013) and Hebei province science and technology research project (20311803D, 9011824Z).

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Authors and Affiliations

  1. Department of Automation, Yanshan University, Qinhuangdao, 066004, China

    Changchun Hua & Jinghua Ning

  2. Department of Automation, Shanghai Jiaotong University, Shanghai, 200240, China

    Xinping Guan

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  1. Changchun Hua
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  2. Jinghua Ning
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  3. Xinping Guan
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Correspondence to Changchun Hua.

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Hua, C., Ning, J. & Guan, X. Controller design for fractional-order interconnected systems with unmodeled dynamics. Nonlinear Dyn 103, 1599–1610 (2021). https://doi.org/10.1007/s11071-020-06177-2

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