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Adaptive fixed-time fault-tolerant control of saturated MIMO nonlinear systems with time-varying state constrains

Adaptive fixed-time fault-tolerant control of saturated MIMO nonlinear systems with time-varying state constrains
Adaptive fixed-time fault-tolerant control of saturated MIMO nonlinear systems with time-varying state constrains

In this paper, the adaptive fixed-time fault-tolerant control (FTC) problem is investigated for a class of uncertain multi-input multi-output (MIMO) nonlinear systems. By utilizing the radial basis function neural networks (NNs), a state observer is designed to estimate the unmeasured states. Then, an observer-based adaptive fixed-time FTC scheme is proposed, which is capable to deal with the unknown actuator faults, asymmetric time-varying state constraints and input saturation simultaneously. It is shown that the boundedness of all the closed-loop signals can be guaranteed, and system output tracks the desired signal to a bounded compact set in fixed time, while the asymmetric time-varying state constraint requirements are not violated. Moreover, the bound of the settling time is independent of the initial states and related to the designed parameters only. Simulation results on a dynamic mechanical system demonstrate the effectiveness of the proposed FTC scheme.

Adaptive fixed-time control, Fault-tolerant control (FTC), Neural network (NN), Nonlinear system, Time-varying state constraints
0924-090X
3463-3483
Fang, Xinpeng
135f800e-5011-4e4f-a483-f0d935ed85a4
Fan, Huijin
c2d58f76-05ea-416d-a5e9-ad971930d613
Liu, Lei
51ddf4cf-b2db-43ad-8e3b-46f0e110f3b2
Wang, Bo
c7e48a2e-8790-4e1f-9740-5b50dd713030
Fang, Xinpeng
135f800e-5011-4e4f-a483-f0d935ed85a4
Fan, Huijin
c2d58f76-05ea-416d-a5e9-ad971930d613
Liu, Lei
51ddf4cf-b2db-43ad-8e3b-46f0e110f3b2
Wang, Bo
c7e48a2e-8790-4e1f-9740-5b50dd713030

Fang, Xinpeng, Fan, Huijin, Liu, Lei and Wang, Bo (2022) Adaptive fixed-time fault-tolerant control of saturated MIMO nonlinear systems with time-varying state constrains. Nonlinear Dynamics, 110 (4), 3463-3483. (doi:10.1007/s11071-022-07784-x).

Record type: Article

Abstract

In this paper, the adaptive fixed-time fault-tolerant control (FTC) problem is investigated for a class of uncertain multi-input multi-output (MIMO) nonlinear systems. By utilizing the radial basis function neural networks (NNs), a state observer is designed to estimate the unmeasured states. Then, an observer-based adaptive fixed-time FTC scheme is proposed, which is capable to deal with the unknown actuator faults, asymmetric time-varying state constraints and input saturation simultaneously. It is shown that the boundedness of all the closed-loop signals can be guaranteed, and system output tracks the desired signal to a bounded compact set in fixed time, while the asymmetric time-varying state constraint requirements are not violated. Moreover, the bound of the settling time is independent of the initial states and related to the designed parameters only. Simulation results on a dynamic mechanical system demonstrate the effectiveness of the proposed FTC scheme.

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More information

Published date: 27 August 2022
Additional Information: Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature B.V.
Keywords: Adaptive fixed-time control, Fault-tolerant control (FTC), Neural network (NN), Nonlinear system, Time-varying state constraints

Identifiers

Local EPrints ID: 495499
URI: http://eprints.soton.ac.uk/id/eprint/495499
ISSN: 0924-090X
PURE UUID: f045bd25-948c-4db3-bc8f-f1c516a25e67
ORCID for Xinpeng Fang: ORCID iD orcid.org/0000-0003-1390-1927

Catalogue record

Date deposited: 14 Nov 2024 18:09
Last modified: 15 Nov 2024 03:13

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Contributors

Author: Xinpeng Fang ORCID iD
Author: Huijin Fan
Author: Lei Liu
Author: Bo Wang

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