Distributed Optimization with Application to Power Systems and Control
Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized-all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization ove...
| Format: | eBook |
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| Language: | English |
| Published: |
Karlsruhe
KIT Scientific Publishing
2022
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| Subjects: | |
| Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
| Summary: | Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized-all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization. |
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| Physical Description: | 1 online resource (226 p.) |
| ISBN: | 9783731511809 KSP/1000144792 |
| Access: | Open Access |