Impulsive Multiconsensus of Second-Order Multiagent Networks Using Sampled Position Data

Abstract

A multiconsensus problem of multiagent networks is solved in this paper, where multiconsensus refers to that the states of multiple agents in each subnetwork asymptotically converge to an individual consistent value when there exist information exchanges among subnetworks. A distributed impulsive protocol is proposed to achieve multiconsensus of second-order multiagent networks in terms of three categories: 1) stationary multiconsensus; 2) the first dynamic multiconsensus; and 3) the second dynamic multiconsensus. This impulsive protocol utilizes only sampled position data and is implemented at sampling instants. For those three categories of multiconsensus, the control parameters in the impulsive protocol are designed, respectively. Moreover, necessary and sufficient conditions are derived, under which each multiconsensus can be reached asymptotically. Several simulations are finally provided to demonstrate the effectiveness of the obtained theoretical results.

Distributed Three‐Dimensional Formation Containment Control of Multiple Unmanned Aerial Vehicle Systems

“…Then, we choose the dwell time T = 0.5s and feedback gains 1 = 0.5, 2 = 2 and 3 = 4 to satisfy the conditions in Theorem 2. Thus, under the control protocol (12) with these parameters, the 3-D trajectories of the multiple UAVs are depicted in Fig. 3a, which illustrates the validity of the theoretical results.…”

“…and similarly, the closed-loop system of (2) with the protocol (12) can be written in a compact form aṡ where t ∈ [ t k , t k+1 )…”

“…As one of the most fundamental and critical problems in cooperative control of multi-agent systems, the consensus problem has been a hot research issue in recent years [9][10][11][12][13][14][15]. Many existing results on consensus consider mainly the leaderless case and the single leader case.…”

“…The formation containment of system (2) under protocol(12). (a) The 3-D trajectories, (b) Evolutions of positions x i , (c) Evolutions of positions y i , (d) Evolutions of positions z i , (e) Evolutions of master UAV v i , (f) Evolutions of slave UAV v i .…”

Attitude‐synchronization flocking of multiple 3‐dimensional nonholonomic agents without position measurement

“…The investigation of the flocking phenomenon is of particular interest to biologists, which helps them to understand and study group behaviors in biological systems, and it is also of particular importance to engineers, which allows them to design simple control algorithms for manmade systems. Besides, flocking is a general framework where one can consider target tracking of networked robotic systems, formation control of networked mobile robots, consensus of multiagent systems,() and so on.…”