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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2022
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2210.12088 |
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| _version_ | 1866916124246933504 |
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| author | Belgioioso, Giuseppe Liao-McPherson, Dominic de Badyn, Mathias Hudoba Bolognani, Saverio Smith, Roy S. Lygeros, John Dörfler, Florian |
| author_facet | Belgioioso, Giuseppe Liao-McPherson, Dominic de Badyn, Mathias Hudoba Bolognani, Saverio Smith, Roy S. Lygeros, John Dörfler, Florian |
| contents | This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) of non-cooperative games. Inspired by the feedback optimization paradigm, the core idea of the proposed approach is to re-purpose classic iterative algorithms for solving generalized equations (e.g., Josephy--Newton, forward-backward splitting) as dynamic feedback controllers by integrating online measurements of the continuous-time nonlinear plant. Sufficient conditions for closed-loop stability and robustness of the algorithm-plant cyber-physical interconnection are derived in a sampled-data setting by combining and tailoring results from (monotone) operator, fixed-point, and nonlinear systems theory. Numerical simulations on smart building automation and competitive supply-chain management are presented to support the theoretical findings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2210_12088 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Online Feedback Equilibrium Seeking Belgioioso, Giuseppe Liao-McPherson, Dominic de Badyn, Mathias Hudoba Bolognani, Saverio Smith, Roy S. Lygeros, John Dörfler, Florian Optimization and Control This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) of non-cooperative games. Inspired by the feedback optimization paradigm, the core idea of the proposed approach is to re-purpose classic iterative algorithms for solving generalized equations (e.g., Josephy--Newton, forward-backward splitting) as dynamic feedback controllers by integrating online measurements of the continuous-time nonlinear plant. Sufficient conditions for closed-loop stability and robustness of the algorithm-plant cyber-physical interconnection are derived in a sampled-data setting by combining and tailoring results from (monotone) operator, fixed-point, and nonlinear systems theory. Numerical simulations on smart building automation and competitive supply-chain management are presented to support the theoretical findings. |
| title | Online Feedback Equilibrium Seeking |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2210.12088 |