Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions

In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capab...

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Main Authors: Kun Yan, Chaobo Chen, Xiaofeng Xu, Qingxian Wu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/4770439
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author Kun Yan
Chaobo Chen
Xiaofeng Xu
Qingxian Wu
author_facet Kun Yan
Chaobo Chen
Xiaofeng Xu
Qingxian Wu
author_sort Kun Yan
collection DOAJ
description In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller.
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issn 1099-0526
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spelling doaj-art-e766ecadd73d43cea7980268fd20e5342025-08-20T02:21:09ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4770439Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control DirectionsKun Yan0Chaobo Chen1Xiaofeng Xu2Qingxian Wu3College of Electronic Information EngineeringCollege of Electronic Information EngineeringCollege of Automation EngineeringCollege of Automation EngineeringIn this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller.http://dx.doi.org/10.1155/2022/4770439
spellingShingle Kun Yan
Chaobo Chen
Xiaofeng Xu
Qingxian Wu
Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
Complexity
title Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
title_full Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
title_fullStr Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
title_full_unstemmed Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
title_short Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions
title_sort neural network based output feedback fault tolerant tracking control for nonlinear systems with unknown control directions
url http://dx.doi.org/10.1155/2022/4770439
work_keys_str_mv AT kunyan neuralnetworkbasedoutputfeedbackfaulttoleranttrackingcontrolfornonlinearsystemswithunknowncontroldirections
AT chaobochen neuralnetworkbasedoutputfeedbackfaulttoleranttrackingcontrolfornonlinearsystemswithunknowncontroldirections
AT xiaofengxu neuralnetworkbasedoutputfeedbackfaulttoleranttrackingcontrolfornonlinearsystemswithunknowncontroldirections
AT qingxianwu neuralnetworkbasedoutputfeedbackfaulttoleranttrackingcontrolfornonlinearsystemswithunknowncontroldirections