4.6 Article

Finite-time adaptive neural command filtered control for pure-feedback time-varying constrained nonlinear systems with actuator faults

期刊

NEUROCOMPUTING
卷 490, 期 -, 页码 193-205

出版社

ELSEVIER
DOI: 10.1016/j.neucom.2021.11.083

关键词

Finite-time adaptive control; Command filter; Actuator failures; Time-varying full state constraints; Unmodeled dynamics

资金

  1. National Natural Science Foundation of China [62073283, 61973266]
  2. Natural Science Foundation of Jiangsu Province [BK20181218]

向作者/读者索取更多资源

This paper investigates finite-time adaptive control (FTAC) for non-affine uncertain constrained nonlinear systems with actuator faults. The state constraints are handled using nonlinear mapping (NM), and an auxiliary dynamical signal is used to handle the unknown dynamic uncertainties of the system. A FTAC strategy is designed based on the converted system using the command filtered backstepping method. The effectiveness of the proposed approach is verified through simulation results.
In this paper, finite-time adaptive control (FTAC) is investigated for non-affine uncertain constrained nonlinear systems with actuator faults. The state constraints are dealt with by using nonlinear mapping (NM), and an auxiliary dynamical signal is used to handle the unknown dynamic uncertainties of the system. Based on the converted system, a FTAC strategy is designed via command filtered backstepping method. By introducing the compensation signals and adding them into the whole Lyapunov function, and with the help of the defined compact set in stability analysis, it is strictly proved that all signals are semi-globally practical finite-time stable (SGPFS) and all the states are within the specified open set. Simulation results verify the effectiveness of the proposed approach. (c) 2021 Elsevier B.V. All rights reserved.

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