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Event‐triggered distributed model predictive control with optimal network topology
Author(s) -
Wei Yongsong,
Li Shaoyuan,
Wu Jing
Publication year - 2020
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4872
Subject(s) - sensitivity (control systems) , computer science , model predictive control , topology (electrical circuits) , scheme (mathematics) , network topology , control theory (sociology) , event (particle physics) , control (management) , distributed computing , mathematics , engineering , computer network , artificial intelligence , mathematical analysis , physics , combinatorics , quantum mechanics , electronic engineering
Summary In this paper, we consider a novel iterative DMPC (distributed model predictive control) scheme for linear discrete‐time systems which are connected by network. Every system is dynamically coupled to neighbors. The proposed method can reduce the communication load without degrading performance compared to cooperative DMPC by sensitivity and information topology analysis. The proposed algorithms are applied in a four‐water‐tanks numerical example, and the simulation results show the effectiveness of the proposed algorithms.