Clustering Switching Regions for Feedback Controllers: A Convex Approach
Coalitional control groups dynamically local controllers into clusters that jointly determine their control actions to maximize control performance while minimizing the cooperation burden. This work presents linear matrix inequalities decision methods to set state-space regions where the switchings...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad Loyola Andalucía |
| Repositorio: | Brújula |
| OAI Identifier: | oai:repositorio.uloyola.es:20.500.12412/4979 |
| Acceso en línea: | https://hdl.handle.net/20.500.12412/4979 https://doi.org/10.1109/TCNS.2021.3084049 |
| Access Level: | acceso abierto |
| Palabra clave: | Distributed control Distributed feed backgains Control by clustering Coalitional control Linear control systems Network topologies Control systems design |
| Sumario: | Coalitional control groups dynamically local controllers into clusters that jointly determine their control actions to maximize control performance while minimizing the cooperation burden. This work presents linear matrix inequalities decision methods to set state-space regions where the switchings between network topologies satisfy properties of interest. In particular, convexity guarantees ellipsoidal switching sets with back-switchings avoided via a dwell time. Also, the convexity property is exploited to analyze the need for coordination at different points of the state space, leading to coordination effort zones. Moreover, by considering invariance , new ellipsoids that confine the state between topologies transitions are provided. Finally, we introduce additional conditions to attain submodularity and, hence, reduce the effort to find optimal solutions. A numerical example is given to illustrate the feasibility of the proposed approach. |
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