Decentralized switched model-based predictive control for distributed large-scale systems with topology switching. (November 2020)

• Record Type: Journal Article
• Authors: Ahandani, Morteza Alinia; Kharrati, Hamed; Hashemzadeh, Farzad; Baradarannia, Mahdi
• Is Part Of: Nonlinear analysis. Volume 38(2020)
• Publication Date: 2020-11
• Subjects: Decentralized switched model-based predictive control -- Distributed switched large-scale system -- Switching signal -- Network topology; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nahs.2020.100912
• Languages: English
• ISSNs: 1751-570X

Abstract

Abstract: This paper proposes a decentralized switched model-based predictive control (DeSwMPC) for handling coupling among subsystems in a distributed switched large-scale system composed of physically interconnected subsystems. In the distributed switched large-scale systems, interactions among subsystems vary over time according to an exogenous input signal named switching signal. The proposed controller aims at stabilizing the origin of the whole closed-loop system while guaranteeing the satisfaction of constraints in the presence of a switching signal. In the DeSwMPC, to consider switching signal effect in variation of network topology, a robust tube-based switched model-based predictive control (SwMPC) is employed as local controller. The SwMPC controllers with switch-robust control invariant (switch-RCI) set as its target set are robust to unknown mode switching. In the employed decentralized model-based predictive control (DeMPC), by assuming interconnections as the additive disturbances, the effect of switch is only reflected on local constraint sets of the nominal subsystems. Simulations are performed on two typical examples. In the first case, the switching times are unknown a priori but the neighborhood sets after switch are known a priori. In the second case, both of them are assumed to be unknown a priori. The obtained results demonstrate that the proposed DeSwMPC satisfies the input and state constraints at all times. They also validate that the closed-loop system converges to the origin.