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Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems
Zhao, Bo1; Li, Yuanchun2; Liu, Derong3
Source PublicationNEUROCOMPUTING
2017-04-26
Issue235Pages:147-156
SubtypeArticle
AbstractIn this paper, a decentralized fault tolerant control (DFTC) scheme is proposed for a class of large-scale nonlinear systems based on self-tuned local feedback gain against partial loss of actuator effectiveness (PLOAE). Consider a large-scale nonlinear system as a set of interconnected subsystems, a decentralized control method is proposed by employing two radial basis function neural networks (RBFNNs) for the fault-free system. Then, the unknown system is identified using RBFNNs. By establishing a decentralized observer, the derived self-tuned local feedback gain is placed before the proposed decentralized controller to guarantee control performance for the subsystem suffering from PLOAE fault. Finally, simulation examples are provided to demonstrate the effectiveness of the present DFTC scheme. The main contributions of this paper are: i) The unknown large-scale nonlinear system can be identified using locally measured states, so the actuator fault can be handled in its local subsystem. It implies that the performance degradation of the faulty subsystem cannot affect the fault-free subsystems. ii) The estimated effectiveness factor is placed before the proposed decentralized scheme. The fault tolerant control structure is simple since it does not need to be redesigned in the case of PLOAE.
KeywordLarge-scale Nonlinear Systems Partial Loss Of Actuator Effectiveness Decentralized Fault Tolerant Control Self-tuned Local Feedback Gain Neural Network
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.neucom.2016.12.063
WOS KeywordDYNAMIC SURFACE CONTROL ; INTERCONNECTED SYSTEMS ; FLIGHT CONTROL ; ACTUATOR EFFECTIVENESS ; TRACKING CONTROL ; NEURAL-NETWORK ; CONTROL DESIGN ; IDENTIFICATION ; FAILURES ; VEHICLE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61233001 ; Scientific and Technological Development Plan Project in Jilin Province of China(20150520112JH ; Beijing Natural Science Foundation(4162065) ; 61273140 ; 20160414033GH) ; 61304086 ; 61374105 ; 61374051 ; 61533017 ; 61503379 ; 61603387 ; U1501251)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000395219700016
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14424
Collection复杂系统管理与控制国家重点实验室_平行控制
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Changchun Univ Technol, Dept Control Sci & Engn, Changchun 130012, Peoples R China
3.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Bo,Li, Yuanchun,Liu, Derong. Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems[J]. NEUROCOMPUTING,2017(235):147-156.
APA Zhao, Bo,Li, Yuanchun,&Liu, Derong.(2017).Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems.NEUROCOMPUTING(235),147-156.
MLA Zhao, Bo,et al."Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems".NEUROCOMPUTING .235(2017):147-156.
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