Consensus seeking via iterative learning for multi‐agent systems with switching topologies and communication time‐delays. (2nd March 2016)

• Record Type: Journal Article
• Authors: Meng, Deyuan; Jia, Yingmin; Du, Junping
• Is Part Of: International journal of robust and nonlinear control. Volume 26:Number 17(2016)
• Page Start: 3772
• Page End: 3790
• Publication Date: 2016-03-02
• Subjects: multi‐agent systems -- consensus seeking -- iterative learning control -- monotonic convergence -- switching topologies -- communication time‐delays.; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.3534
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: This paper deals with the high‐precision consensus seeking problem of multi‐agent systems when they are subject to switching topologies and varying communication time‐delays. By combining the iterative learning control (ILC) approach, a distributed consensus seeking algorithm is presented based on only the relative information between every agent and its local (or nearest) neighbors. All agents can be enabled to achieve consensus exactly on a common output trajectory over a finite time interval. Furthermore, conditions are proposed to guarantee both exponential convergence and monotonic convergence for the resulting ILC processes of multi‐agent consensus systems. In particular, the linear matrix inequality technique is employed to formulate the established convergence conditions, which can directly give formulas for the gain matrix design. An illustrative example is included to validate the effectiveness of the proposed ILC‐motivated consensus seeking algorithm. Copyright © 2016 John Wiley & Sons, Ltd.