Publication
Economic model predictive control based on a periodicity constraint
Journal Article (2018)
Journal
Journal of Process Control
Pages
226-239
Volume
68
Doc link
https://doi.org/10.1016/j.jprocont.2018.06.008
File
Authors
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Wang, Ye
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Salvador, José Ramón
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Muñoz de la Peña, David
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Puig Cayuela, Vicenç
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Cembrano Gennari, Gabriela
Projects associated
Abstract
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.
Categories
control theory.
Scientific reference
Y. Wang, J.R. Salvador, D. Muñoz, V. Puig and G. Cembrano. Economic model predictive control based on a periodicity constraint. Journal of Process Control, 68: 226-239, 2018.
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