Journal
NEUROCOMPUTING
Volume 399, Issue -, Pages 86-95Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2020.02.089
Keywords
High-order nonlinear systems; Full-state constraints; Adaptive finite-time fuzzy control; Feasibility conditions
Categories
Funding
- National Key R&D Program of China [2018YFC2001700]
- Taishan Scholar Project of Shandong Province of China [ts201712040]
- 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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