Adaptive Decentralized Control Scheme for a Stochastic Interconnected System

Adaptive Decentralized Control Scheme for a Stochastic Interconnected System

This work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapun...

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Main Authors: Xiaoli Jiang, Siqi Liu, Mingyue Liu, Li Yang, Lina Liu
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/6018398
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spelling doaj-8bce27c299504f699c166bbfe6dd20d92020-11-25T03:27:48ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/60183986018398Adaptive Decentralized Control Scheme for a Stochastic Interconnected SystemXiaoli Jiang0Siqi Liu1Mingyue Liu2Li Yang3Lina Liu4College of Mathematics and Physics, Bohai University, Jinzhou 121013, Liaoning, ChinaCollege of Mathematics and Physics, Bohai University, Jinzhou 121013, Liaoning, ChinaCollege of Mathematics and Physics, Bohai University, Jinzhou 121013, Liaoning, ChinaCollege of Mathematics and Physics, Bohai University, Jinzhou 121013, Liaoning, ChinaSchool of Electronic and Information Engineering, Soochow University, Suzhou, Jiangsu 215006, ChinaThis work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapunov function and backstepping technology together, an adaptive decentralized controller is established, and we can construct the boundedness of all signals in the closed-loop structure through the controller, which can drive the formation of a given reference signal. In the end, the effectiveness of the presented strategy is referred to a simulation example.http://dx.doi.org/10.1155/2020/6018398
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoli Jiang
Siqi Liu
Mingyue Liu
Li Yang
Lina Liu
spellingShingle Xiaoli Jiang
Siqi Liu
Mingyue Liu
Li Yang
Lina Liu
Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
Complexity
author_facet Xiaoli Jiang
Siqi Liu
Mingyue Liu
Li Yang
Lina Liu
author_sort Xiaoli Jiang
title Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
title_short Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
title_full Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
title_fullStr Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
title_full_unstemmed Adaptive Decentralized Control Scheme for a Stochastic Interconnected System
title_sort adaptive decentralized control scheme for a stochastic interconnected system
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2020-01-01
description This work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapunov function and backstepping technology together, an adaptive decentralized controller is established, and we can construct the boundedness of all signals in the closed-loop structure through the controller, which can drive the formation of a given reference signal. In the end, the effectiveness of the presented strategy is referred to a simulation example.
url http://dx.doi.org/10.1155/2020/6018398
work_keys_str_mv AT xiaolijiang adaptivedecentralizedcontrolschemeforastochasticinterconnectedsystem
AT siqiliu adaptivedecentralizedcontrolschemeforastochasticinterconnectedsystem
AT mingyueliu adaptivedecentralizedcontrolschemeforastochasticinterconnectedsystem
AT liyang adaptivedecentralizedcontrolschemeforastochasticinterconnectedsystem
AT linaliu adaptivedecentralizedcontrolschemeforastochasticinterconnectedsystem
_version_ 1715208392326250496

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