Abstract
This article presents a novel distributed adaptive predictive controller based on supervised multiple models. The local control agents embed a linear model based predictive control (MPC) algorithm and a coordination algorithm that relies on the Alternating Direction Method of Multipliers (ADMM) distributed optimization algorithm. In order to illustrate the controller proposed, this one is applied to the coordinated control of steam flow and pressure in a biomass thermal power plant. A comparison is made with two other distributed adaptive controllers, with coordination based on a game procedure, one with LQG, and the other with local MPC controllers.
This work was supported by national funds through FCT, Fundação para a Ciência e a tecnologia, Portugal, under project UIBD/50021/2020 and by POR Lisboa, LISBOA-01-0145-FEDER-031411 (project HARMONY).
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Nabais, M., Lemos, J.M. (2021). Distributed Adaptive Predictive Control Based on Switched Multiple Models and ADMM. In: Gonçalves, J.A., Braz-César, M., Coelho, J.P. (eds) CONTROLO 2020. CONTROLO 2020. Lecture Notes in Electrical Engineering, vol 695. Springer, Cham. https://doi.org/10.1007/978-3-030-58653-9_24
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