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Robust fault-tolerant prescribed performance tracking for uncertain switched pure-feedback nonlinear systems under arbitrary switching

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  • Seung Woo Lee
  • Sung Jin Yoo

Abstract

This paper presents a model-free prescribed performance design methodology for the robust fault-tolerant tracking (RFTT) of uncertain switched pure-feedback nonlinear systems under arbitrary switching. Unexpected faults in switched non-affine nonlinearities and in an actuator are considered. Using the prescribed performance design and the common Lyapunov function method, a common RFTT scheme is proposed to ensure that the tracking error remains within preassigned performance bounds and finally converges to a preselected neighbourhood of the origin, regardless of arbitrary switching and unexpected faults. Contrary to existing results in the literature, the proposed methodology does not require fault compensation mechanisms such as adaptive techniques and function approximators using neural networks or fuzzy systems. Thus, the structure of the proposed RFTT scheme is simpler than that of the existing control schemes. Moreover, the proposed approach can predesign the transient performance bounds at the instants when switching and faults occur. Finally, the simulation results are provided to demonstrate the effectiveness of the proposed theoretical approach.

Suggested Citation

  • Seung Woo Lee & Sung Jin Yoo, 2017. "Robust fault-tolerant prescribed performance tracking for uncertain switched pure-feedback nonlinear systems under arbitrary switching," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(3), pages 578-586, February.
  • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:3:p:578-586
    DOI: 10.1080/00207721.2016.1193259
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    Cited by:

    1. Xue, Huanbin & Xu, Xiaohui & Zhang, Jiye & Yang, Xiaopeng, 2019. "Robust stability of impulsive switched neural networks with multiple time delays," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 456-475.

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