Distributed Economic MPC with Adaptive Terminal Weights

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OriginalspracheEnglisch
Seiten (von - bis)99-106
Seitenumfang8
FachzeitschriftIFAC-PapersOnLine
Jahrgang58
Ausgabenummer18
PublikationsstatusVeröffentlicht - 25 Sept. 2024
Veranstaltung8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024 - Kyoto, Japan
Dauer: 21 Aug. 202424 Aug. 2024

Abstract

We develop a distributed economic model predictive control (MPC) scheme with generalized terminal constraints and self-tuning terminal weights for multi-agent systems. We state conditions on the terminal weights' adaption such that an average performance bound holds for the closed-loop system. In addition, we discuss an update law for the terminal weights for which the best reachable equilibria need not be computed in each time step, but which depends only on suboptimal reachable equilibria, e.g. obtained by performing a few steps of a distributed optimization algorithm in each time step.

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Distributed Economic MPC with Adaptive Terminal Weights. / Köhler, Matthias; Müller, Matthias A.; Allgöwer, Frank.
in: IFAC-PapersOnLine, Jahrgang 58, Nr. 18, 25.09.2024, S. 99-106.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Köhler, M, Müller, MA & Allgöwer, F 2024, 'Distributed Economic MPC with Adaptive Terminal Weights', IFAC-PapersOnLine, Jg. 58, Nr. 18, S. 99-106. https://doi.org/10.1016/j.ifacol.2024.09.016
Köhler M, Müller MA, Allgöwer F. Distributed Economic MPC with Adaptive Terminal Weights. IFAC-PapersOnLine. 2024 Sep 25;58(18):99-106. doi: 10.1016/j.ifacol.2024.09.016
Köhler, Matthias ; Müller, Matthias A. ; Allgöwer, Frank. / Distributed Economic MPC with Adaptive Terminal Weights. in: IFAC-PapersOnLine. 2024 ; Jahrgang 58, Nr. 18. S. 99-106.
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AU - Köhler, Matthias

AU - Müller, Matthias A.

AU - Allgöwer, Frank

N1 - Publisher Copyright: Copyright © 2024 The Authors.

PY - 2024/9/25

Y1 - 2024/9/25

N2 - We develop a distributed economic model predictive control (MPC) scheme with generalized terminal constraints and self-tuning terminal weights for multi-agent systems. We state conditions on the terminal weights' adaption such that an average performance bound holds for the closed-loop system. In addition, we discuss an update law for the terminal weights for which the best reachable equilibria need not be computed in each time step, but which depends only on suboptimal reachable equilibria, e.g. obtained by performing a few steps of a distributed optimization algorithm in each time step.

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KW - distributed MPC

KW - economic MPC

KW - multi-agent systems

KW - nonlinear systems

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