title: Distributed leader-following finite-time consensus control for linear multiagent systems under switching topology.
abstract: This paper investigates the finite-time consensus problem of leader-following multiagent systems. The dynamical models for all following agents and the leader are assumed the same general form of linear system, and the interconnection topology among the agents is assumed to be switching and undirected. We mostly consider the continuous-time case. By assuming that the states of neighbouring agents are known to each agent, a sufficient condition is established for finite-time consensus via a neighbor-based state feedback protocol. While the states of neighbouring agents cannot be available and only the outputs of neighbouring agents can be accessed, the distributed observer-based consensus protocol is proposed for each following agent. A sufficient condition is provided in terms of linear matrix inequalities to design the observer-based consensus protocol, which makes the multiagent systems achieve finite-time consensus under switching topologies. Then, we discuss the counterparts for discrete-time case. Finally, we provide an illustrative example to show the effectiveness of the design approach.
authors.affiliation: Wenzhou Vocational College of Science & Technology, Zhejiang 325006, China ; College of Information Engineering, Zhejiang University of Technology, Zhejiang 310023, China.
authors.forename: Xiaole
authors.initials: X
authors.lastname: Xu
authors.affiliation: College of Information Engineering, Zhejiang University of Technology, Zhejiang 310023, China.
authors.forename: Shengyong
authors.initials: S
authors.lastname: Chen
authors.affiliation: Institute of Intelligent Systems and Decision, Wenzhou University, Zhejiang 325027, China.
authors.forename: Lixin
authors.identifier: 0000-0002-6691-7992
authors.initials: L
authors.lastname: Gao
mesh_terms: D001185:Artificial Intelligence; D003661:Decision Support Techniques; D005246:Feedback; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted