Title: Stability analysis in cooperative distributed model predictive control

Authors: Jianhong Wang; Ricardo A. Ramirez-Mendoza; Jorge De J. Lozoya Santos

Addresses: School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico ' School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico ' School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico

Abstract: Due to cooperative distributed model predictive control scheme is widely applied in large scale networks of systems, so asymptotic stability is a very important index for measuring the performance of cooperative distributed model predictive control. Based on the obvious inequality from classical Lyapunov stability condition, we derive a set of linear matrix inequalities to replace the common inequalities by using Schur complement and S-procedure. Furthermore when combining local state and input constraint sets, a set of more complex linear matrix inequalities is used to guarantee the asymptotically stable for cooperative distributed model predictive control.

Keywords: cooperative distributed; model predictive control; stability; linear matrix inequality.

DOI: 10.1504/IJSSE.2019.104187

International Journal of System of Systems Engineering, 2019 Vol.9 No.4, pp.371 - 383

Received: 14 Nov 2018
Accepted: 04 Jul 2019
Published online: 20 Dec 2019 *

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