Set-membership-based distributed moving horizon estimation of large-scale systems
This work is concerned with the design of a two-step distributed state estimation scheme for large-scale systems in the presence of unknown-but-bounded disturbances and noise. The set-membership approach is employed to construct a compact set containing the states consistent with system measurements...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/376839 |
| Acceso en línea: | https://hdl.handle.net/2117/376839 https://dx.doi.org/10.1016/j.isatra.2021.10.036 |
| Access Level: | acceso abierto |
| Palabra clave: | Sistemes a gran escala Control theory Optimisation Large-scale systems Distributed state estimation Moving horizon estimation Set-membership Optimality condition decomposition Community detection Large scale systems Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | This work is concerned with the design of a two-step distributed state estimation scheme for large-scale systems in the presence of unknown-but-bounded disturbances and noise. The set-membership approach is employed to construct a compact set containing the states consistent with system measurements and bounded noise and disturbances. The tightened feasible region is then provided to a moving horizon estimator that determines the optimal state estimates. Partitioning of the overall problem and coordination of the resulting subproblems are achieved using decomposition of the optimality conditions and community detection. The proposed strategy is tested on a case study based on a reactor–separator system widely used in the literature. Its performance is compared to those of centralized and distributed (without set-membership) implementations, allowing to highlight its effectiveness. |
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