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Adaptive Fuzzy Output-Feedback Control for Switched Nonlinear Systems with Arbitrary Switchings

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Abstract

This paper investigates the adaptive fuzzy output-feedback control problem for single-input and single-output switched uncertain nonlinear systems. The addressed systems in this paper have the characteristics of arbitrary switchings, unknown nonlinear dynamics and immeasurable states. A common state observer is designed independent of switching signals. Fuzzy logic systems are utilized to approximate unknown lumped nonlinear dynamics. Based on the framework of backstepping design technique, an adaptive fuzzy output-feedback control scheme is developed. By using the common Lyapunov function theory, the stability of the closed-loop system is proved. The proposed control scheme does not need the assumptions that the states of the controlled system are available for measurement and that the switching signals satisfy the average dwell time. Moreover, it can guarantee that all the closed-loop signals are bounded, and the system output eventually converges to a small neighborhood of the origin. Finally, simulation studies are provided to further check the effectiveness of the proposed control scheme.

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Authors and Affiliations

  1. College of Science, Liaoning University of Technology, 169 Shiying Street, Guta District, Jinzhou, Liaoning, People’s Republic of China

    Yongming Li & Shaocheng Tong

  2. Engineering Research Center of Key Technology on Automobile and Its Parts, Liaoning University of Technology, 169 Shiying Street, Guta District, Jinzhou, Liaoning, People’s Republic of China

    Yongming Li & Shaocheng Tong

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  1. Yongming Li
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  2. Shaocheng Tong
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Correspondence to Yongming Li.

Additional information

This work is supported by the National Natural Science Foundation of China (Nos. 61573175, 61374113), and the Program for Liaoning Excellent Talents in University (LJQ2015048).

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Li, Y., Tong, S. Adaptive Fuzzy Output-Feedback Control for Switched Nonlinear Systems with Arbitrary Switchings. Circuits Syst Signal Process 35, 3152–3171 (2016). https://doi.org/10.1007/s00034-015-0196-0

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  • DOI: https://doi.org/10.1007/s00034-015-0196-0

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