Time-Varying Scheme for Noncentralized Model Predictive Control of Large-Scale Systems
The noncentralized model predictive control (NC-MPC) framework in this paper refers to any distributed, hierarchical, or decentralized model predictive controller (or a combination of them) the structure of which can change over time and the control actions of which are not obtained based on a centr...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2015 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositório: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/58674 |
| Acesso em linha: | http://hdl.handle.net/11441/58674 https://doi.org/10.1155/2015/560702 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Noncentralized Model Predictive Control of Large-Scale Time-Varying Scheme Large-Scale Systems |
| Resumo: | The noncentralized model predictive control (NC-MPC) framework in this paper refers to any distributed, hierarchical, or decentralized model predictive controller (or a combination of them) the structure of which can change over time and the control actions of which are not obtained based on a centralized computation.Within this framework, we propose suitable onlinemethods to decide which information is shared and how this information is used between the different local predictive controllers operating in a decentralized, distributed, and/or hierarchical way. Evaluating all the possible structures of the NC-MPC controller leads to a combinatorial optimization problem.Therefore, we also propose heuristic reduction methods, to keep the number of NC-MPC problems tractable to be solved. To show the benefits of the proposed framework, a case study of a set of coupled water tanks is presented. |
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