Cooperative distributed MPC for tracking
This paper proposes a cooperative distributed linear model predictive control strategy for tracking changing setpoints, applicable to any finite number of subsystems. The proposed controller is able to drive the whole system to any admissible setpoint in an admissible way, ensuring feasibility under...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/25197 |
| Acceso en línea: | http://hdl.handle.net/11336/25197 |
| Access Level: | acceso abierto |
| Palabra clave: | Model Predictive Control Distributed Control Cooperative Games Setpoint Tracking Stability https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
| Sumario: | This paper proposes a cooperative distributed linear model predictive control strategy for tracking changing setpoints, applicable to any finite number of subsystems. The proposed controller is able to drive the whole system to any admissible setpoint in an admissible way, ensuring feasibility under any change of setpoint. It also provides a larger domain of attraction than standard distributed MPC for regulation, due to the particular terminal constraint. Moreover, the controller ensures convergence to the centralized optimum, even in case of coupled constraints. This is possible thanks to the warm start used to initialize the optimization Algorithm, and to the design of the cost function, which integrates a Steady State Target Optimizer (SSTO). The controller is applied to a real 4 tanks plant. |
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