Advances in Artificial Intelligence Methods Applications in Industrial Control Systems
The motivation for the present reprint is to provide an overview of novel applications of AI methods to industrial control systems by means of selected best practices in highlighting how such methodologies can be used to improve the production systems self-learning capacities, their overall performa...
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| Formaat: | Online |
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| Taal: | Engels |
| Gepubliceerd in: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Onderwerpen: | |
| Online toegang: | ONIX_20230405_9783036568089_199 |
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| _version_ | 1869516722433687552 |
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| collection | Directory of Open Access Books |
| description | The motivation for the present reprint is to provide an overview of novel applications of AI methods to industrial control systems by means of selected best practices in highlighting how such methodologies can be used to improve the production systems self-learning capacities, their overall performance, the related process and product quality, the optimal use of resources and the industrial systems safety, and resilience to varying boundary conditions and production requests. By means of its seven scientific contributions, the present reprint illustrates the increasing added value of the introduction of AI methods for improving the performance of control solutions with reference to different control and automation problems in different industrial applications and sectors, ranging from single manipulators or small unmanned ground vehicles up to complex manufacturing. Additionally, the role of AI to improve the performance of relevant engineering methodologies and digital instruments, such as cyberphysical systems, digital twins, and human–robot collaboration, are also effectively addressed in the included contributions. |
| format | Online |
| id | doab-20.500.12854ir-98920 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-989202024-04-09T23:15:58Z Advances in Artificial Intelligence Methods Applications in Industrial Control Systems Carpanzano, Emanuele policy iteration uncertain nonlinear system robust control adaptive optimal control digital twin human robot collaboration reconfiguration interoperability industry 4.0 manufacturing execution system cyber-physical production system OPC UA reinforcement learning decentralized control multi-agent continuous control robotic grasping policy optimization multi-dimensional Taylor network predictive control nonlinear system SUGV predictive model NARX-ANN-based models modified SP controller design irrigation main canal pool automation system identification management of water resources control systems industrial automation artificial intelligence machine learning self-learning machine tools adaptive production systems n/a 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 The motivation for the present reprint is to provide an overview of novel applications of AI methods to industrial control systems by means of selected best practices in highlighting how such methodologies can be used to improve the production systems self-learning capacities, their overall performance, the related process and product quality, the optimal use of resources and the industrial systems safety, and resilience to varying boundary conditions and production requests. By means of its seven scientific contributions, the present reprint illustrates the increasing added value of the introduction of AI methods for improving the performance of control solutions with reference to different control and automation problems in different industrial applications and sectors, ranging from single manipulators or small unmanned ground vehicles up to complex manufacturing. Additionally, the role of AI to improve the performance of relevant engineering methodologies and digital instruments, such as cyberphysical systems, digital twins, and human–robot collaboration, are also effectively addressed in the included contributions. 2023-04-05T12:59:08Z 2023-04-05T12:59:08Z 2023 book ONIX_20230405_9783036568089_199 9783036568089 9783036568096 https://directory.doabooks.org/handle/20.500.12854/98920 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/6973 https://mdpi.com/books/pdfview/book/6973 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-6809-6 10.3390/books978-3-0365-6809-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036568089 9783036568096 150 Basel open access |
| spellingShingle | policy iteration uncertain nonlinear system robust control adaptive optimal control digital twin human robot collaboration reconfiguration interoperability industry 4.0 manufacturing execution system cyber-physical production system OPC UA reinforcement learning decentralized control multi-agent continuous control robotic grasping policy optimization multi-dimensional Taylor network predictive control nonlinear system SUGV predictive model NARX-ANN-based models modified SP controller design irrigation main canal pool automation system identification management of water resources control systems industrial automation artificial intelligence machine learning self-learning machine tools adaptive production systems n/a 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 Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title | Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title_full | Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title_fullStr | Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title_full_unstemmed | Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title_short | Advances in Artificial Intelligence Methods Applications in Industrial Control Systems |
| title_sort | advances in artificial intelligence methods applications in industrial control systems |
| topic | policy iteration uncertain nonlinear system robust control adaptive optimal control digital twin human robot collaboration reconfiguration interoperability industry 4.0 manufacturing execution system cyber-physical production system OPC UA reinforcement learning decentralized control multi-agent continuous control robotic grasping policy optimization multi-dimensional Taylor network predictive control nonlinear system SUGV predictive model NARX-ANN-based models modified SP controller design irrigation main canal pool automation system identification management of water resources control systems industrial automation artificial intelligence machine learning self-learning machine tools adaptive production systems n/a 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 | policy iteration uncertain nonlinear system robust control adaptive optimal control digital twin human robot collaboration reconfiguration interoperability industry 4.0 manufacturing execution system cyber-physical production system OPC UA reinforcement learning decentralized control multi-agent continuous control robotic grasping policy optimization multi-dimensional Taylor network predictive control nonlinear system SUGV predictive model NARX-ANN-based models modified SP controller design irrigation main canal pool automation system identification management of water resources control systems industrial automation artificial intelligence machine learning self-learning machine tools adaptive production systems n/a 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_20230405_9783036568089_199 |