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Neural event-triggered optimal filtering co-design of Markovian jump systems with hidden mode detections | |
Ma, Chao1,2; Lu, Yanfeng2![]() ![]() | |
发表期刊 | TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
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ISSN | 0142-3312 |
2023-01-24 | |
页码 | 11 |
摘要 | The modified H-infinity filtering problem for a class of Markovian jump systems with unknown nonlinear dynamics is investigated in the work by developing the neural event-triggered filter co-design method. Moreover, the true system modes are assumed to be inaccessible such that the estimated jumping modes are utilized for the mode-dependent filters. In particular, a novel event-triggered mechanism is introduced to improve filtering communication efficiency, where the unknown nonlinearity approximation is conducted by a neural network. By virtue of employing Lyapunov-Krasovskii method, sufficient filtering conditions are constructed to ensure the optimal H-infinity performance under the mean-square framework, based on which desired mode-dependent filter gains, event-triggering, and neural network parameters are co-designed with an aid of matrix techniques. Illustrative simulations with two practical examples are finally carried out to validate the usefulness and advantages of our developed approach. |
关键词 | Markovian jump system neural event-triggered scheme optimal filtering unknown nonlinearity hidden mode detections |
DOI | 10.1177/01423312221143269 |
关键词[WOS] | STABILITY ANALYSIS ; NETWORK CONTROL ; TIME ; INEQUALITY ; DELAY |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62173326] ; National Key Research and Development Plan of Chinaunder[2020AAA0105900] ; BeijingNatural Science Foundation[L211023] |
项目资助者 | National Natural Science Foundation of China ; National Key Research and Development Plan of Chinaunder ; BeijingNatural Science Foundation |
WOS研究方向 | Automation & Control Systems ; Instruments & Instrumentation |
WOS类目 | Automation & Control Systems ; Instruments & Instrumentation |
WOS记录号 | WOS:000922953100001 |
出版者 | SAGE PUBLICATIONS LTD |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 人机混合智能 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51408 |
专题 | 多模态人工智能系统全国重点实验室 |
通讯作者 | Wu, Wei |
作者单位 | 1.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ma, Chao,Lu, Yanfeng,Wu, Wei. Neural event-triggered optimal filtering co-design of Markovian jump systems with hidden mode detections[J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,2023:11. |
APA | Ma, Chao,Lu, Yanfeng,&Wu, Wei.(2023).Neural event-triggered optimal filtering co-design of Markovian jump systems with hidden mode detections.TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,11. |
MLA | Ma, Chao,et al."Neural event-triggered optimal filtering co-design of Markovian jump systems with hidden mode detections".TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL (2023):11. |
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