Barrier Lypunov functions-based nonsingular fixed-time switching control for strict-feedback nonlinear dynamics with full state constraints

Wenqian Zhang, Wenhan Dong, Maolong Lv, Zongcheng Liu, Yang Zhou, Haoming Feng

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This work proposes a nonsingular adaptive fixed-time switching control method for a class of strict-feedback nonlinear dynamics subject to full state constraints. The peculiarity of this design lies in overcoming the singularity issue that typically appears in the existing backstepping-based fixed-time control methods caused by the iterative differentiation of fractional power terms as tracking errors approach to zero, while guaranteeing the nonviolation of full state constraints. Crucial in solving such singularity issue is to skillfully introduce a smooth switching between fractional power and integer power terms, which guarantees that fractional power term is confined within a positive interval all the time. An asymmetric time-varying barrier Lyapunov function is delicately incorporated into control design, rendering state variables to be within prescribed time-varying bounds. Besides, radial basis function neural network is employed to handle system unknown nonlinearities. It is rigorously proved that all the closed-loop signals eventually converge to small regions around origin within fixed-time. Comparative simulation results are finally given to validate the effectiveness and superiority of the proposed control strategy.

Original languageEnglish
Pages (from-to)7862-7885
Number of pages24
JournalInternational Journal of Robust and Nonlinear Control
Volume31
Issue number16
DOIs
Publication statusPublished - 2021

Keywords

  • adaptive backstepping control
  • fixed-time stability
  • switching control
  • time-varying state constraints

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