Economic model predictive control based on a periodicity constraint

This paper addresses a novel economic model predictive control (MPC) formulation based on a periodicity constraint to achieve an optimal periodic operation for discrete-time linear systems. The proposed control strategy does not rely on forcing the terminal state by means of a terminal equality cons...

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Detalhes bibliográficos
Autores: Wang, Ye, Salvador Ortiz, José Ramón, Muñoz de la Peña Sequedo, David, Puig, Vicenç, Cembrano, Gabriela
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/86985
Acesso em linha:https://hdl.handle.net/11441/86985
https://doi.org/10.1016/j.jprocont.2018.06.008
Access Level:acceso abierto
Palavra-chave:Economic model predictive control
Periodicity constraint
Recursive feasibility
Convergence analysis
Water distribution networks
Descrição
Resumo:This paper addresses a novel economic model predictive control (MPC) formulation based on a periodicity constraint to achieve an optimal periodic operation for discrete-time linear systems. The proposed control strategy does not rely on forcing the terminal state by means of a terminal equality constraint and hence it does not require a priori knowledge of a periodic steady trajectory. Instead, at each sampling time step the economic cost function is optimized based on a periodicity constraint over all the periodic trajectories that include the current state. The recursive feasibility and the closed-loop convergence to a periodic steady trajectory are discussed. Moreover, an optimality certificate of this steady trajectory is provided based on the Karush–Kuhn–Tucker (KKT) optimality conditions. Finally, an application to a well-known water distribution network benchmark is presented to demonstrate the proposed economic MPC in which the closed-loop simulation results obtained with a linear model and a virtual–reality simulator are both provided