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Self-tuned local feedback gain based decentralized fault tolerant control for a class of large-scale nonlinear systems | |
Zhao, Bo1![]() | |
发表期刊 | NEUROCOMPUTING
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2017-04-26 | |
期号 | 235页码:147-156 |
文章类型 | Article |
摘要 | In 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. |
关键词 | Large-scale Nonlinear Systems Partial Loss Of Actuator Effectiveness Decentralized Fault Tolerant Control Self-tuned Local Feedback Gain Neural Network |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1016/j.neucom.2016.12.063 |
关键词[WOS] | DYNAMIC SURFACE CONTROL ; INTERCONNECTED SYSTEMS ; FLIGHT CONTROL ; ACTUATOR EFFECTIVENESS ; TRACKING CONTROL ; NEURAL-NETWORK ; CONTROL DESIGN ; IDENTIFICATION ; FAILURES ; VEHICLE |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National 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研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000395219700016 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14424 |
专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
作者单位 | 1.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 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 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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