4.6 Article

Adaptive finite-time fuzzy control of full-state constrained high-order nonlinear systems without feasibility conditions and its application

Journal

NEUROCOMPUTING
Volume 399, Issue -, Pages 86-95

Publisher

ELSEVIER
DOI: 10.1016/j.neucom.2020.02.089

Keywords

High-order nonlinear systems; Full-state constraints; Adaptive finite-time fuzzy control; Feasibility conditions

Funding

  1. National Key R&D Program of China [2018YFC2001700]
  2. Taishan Scholar Project of Shandong Province of China [ts201712040]
  3. National Natural Science Foundation of China [61673242]

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This paper investigates adaptive finite-time fuzzy control for full-state constrained high-order nonlinear systems. Fuzzy logic systems are employed to relax growth assumptions imposed on unknown system nonlinearities. By integrating a nonlinear state-dependent transformation into control design, full-state constraints can be handled without imposing feasibility conditions on virtual controllers. It is rigorously proved that fuzzy approximation is valid based on a compact set, full-state constraints aren't violated for all time. Besides, the solution of the closed-loop system is semi-global practical finite-time stable, and the tracking error converges to an adjustable compact set around the origin in finite-time. Two examples show the advantages of this control scheme. (C) 2020 Elsevier B.V. All rights reserved.

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