Fault Detection and State Estimation in Automatic Control
Fault detection and state estimation are essential tasks for ensuring the reliability, safety and performance of automatic control systems. They play a critical role in detecting and isolating faults quickly and accurately, enabling timely corrective action and preventing system failures. The field...
保存先:
| フォーマット: | Online |
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| 言語: | 英語 |
| 出版事項: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| 主題: | |
| オンライン･アクセス: | ONIX_20240108_9783036597560_54 |
| タグ: |
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| _version_ | 1869520356389158912 |
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| collection | Directory of Open Access Books |
| description | Fault detection and state estimation are essential tasks for ensuring the reliability, safety and performance of automatic control systems. They play a critical role in detecting and isolating faults quickly and accurately, enabling timely corrective action and preventing system failures. The field of fault detection and state estimation has seen significant advances in recent years, driven by the integration of advanced methodologies with cutting-edge technologies, in particular artificial intelligence and deep learning. These techniques have demonstrated remarkable capabilities in fault diagnosis, state estimation and fault-tolerant control, especially in complex multi-sensor systems. This Special Issue highlights and discusses the design and application of fault detection algorithms, the design and application of state estimation methods, the design and application of machine learning algorithms, the analysis of automatic control system characteristics, and the design and application of intelligent control systems. Nevertheless, many challenges remain and require attention, including scalability, computational efficiency, online implementation, fault isolation, fault recovery and fault-tolerant control. Additional research efforts are therefore essential to advance both the theory and practice of this critical task. |
| format | Online |
| id | doab-20.500.12854ir-132395 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1323952024-04-09T23:16:05Z Fault Detection and State Estimation in Automatic Control Du, Sheng Wang, Wei Fu, Hao Wan, Xiongbo Intelligent Control Intelligent Modeling Computational Intelligence Artificial Intelligence State Estimation Fault Detection thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Fault detection and state estimation are essential tasks for ensuring the reliability, safety and performance of automatic control systems. They play a critical role in detecting and isolating faults quickly and accurately, enabling timely corrective action and preventing system failures. The field of fault detection and state estimation has seen significant advances in recent years, driven by the integration of advanced methodologies with cutting-edge technologies, in particular artificial intelligence and deep learning. These techniques have demonstrated remarkable capabilities in fault diagnosis, state estimation and fault-tolerant control, especially in complex multi-sensor systems. This Special Issue highlights and discusses the design and application of fault detection algorithms, the design and application of state estimation methods, the design and application of machine learning algorithms, the analysis of automatic control system characteristics, and the design and application of intelligent control systems. Nevertheless, many challenges remain and require attention, including scalability, computational efficiency, online implementation, fault isolation, fault recovery and fault-tolerant control. Additional research efforts are therefore essential to advance both the theory and practice of this critical task. 2024-01-08T14:46:44Z 2024-01-08T14:46:44Z 2023 book ONIX_20240108_9783036597560_54 9783036597560 9783036597577 https://directory.doabooks.org/handle/20.500.12854/132395 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/8420 https://mdpi.com/books/pdfview/book/8420 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-9757-7 10.3390/books978-3-0365-9757-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036597560 9783036597577 248 Basel open access |
| spellingShingle | Intelligent Control Intelligent Modeling Computational Intelligence Artificial Intelligence State Estimation Fault Detection thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Fault Detection and State Estimation in Automatic Control |
| title | Fault Detection and State Estimation in Automatic Control |
| title_full | Fault Detection and State Estimation in Automatic Control |
| title_fullStr | Fault Detection and State Estimation in Automatic Control |
| title_full_unstemmed | Fault Detection and State Estimation in Automatic Control |
| title_short | Fault Detection and State Estimation in Automatic Control |
| title_sort | fault detection and state estimation in automatic control |
| topic | Intelligent Control Intelligent Modeling Computational Intelligence Artificial Intelligence State Estimation Fault Detection thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | Intelligent Control Intelligent Modeling Computational Intelligence Artificial Intelligence State Estimation Fault Detection thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20240108_9783036597560_54 |