Stationary Consensus of Asynchronous Discrete-Time Second-Order Multi-Agent Systems Under Switching Topology

Abstract

Abstract-This paper is concerned with the asynchronous consensus problem of discrete-time second-order multi-agent system under dynamically changing communication topology, in which the asynchrony means that each agent detects the neighbors' state information to update its state information by its own clock. It is not assumed that the agents' clocks are synchronized. Nor is it assumed that the time sequence over which each agent update its state information is evenly spaced. By using tools from graph theory and nonnegative matrix theory, particularly the product properties of row-stochastic matrices from an infinite set, we finally show that essentially the same result as that for the synchronous discrete-time system holds in the face of asynchronous setting. This generalizes the existing result to a very general case.

Consensus seeking of delayed high-order multi-agent systems with predictor-based algorithm

“…Consensus convergence of synchronously-coupled algorithm depends on the communication delay strictly for the multi-agent systems under fixed [19,29,33,37] or switched topologies [4,6,17,24,30,32,38]. With proper control parameters, differently, the stationary consensus algorithms in asynchronously-coupled form is convergent without any relationship to the communication delay value for the first-order, second-order and high-order agents [10,11,12,21,27]. However, dynamical consensus algorithm in asynchronously-coupled form just drives second-order or highorder dynamic agents to reach the stationary consensus asymptotically [2,14,18,25,31], and the consensus convergence is strictly dependent on the communication delay.…”

“…By simulation, the largest communication delay that the system can tolerate is τ max = 0.96(s). Investigating the agents (25) under the predictor-based consensus algorithm (5) with 0 < τ 0 = τ , we choose τ 0 = 0.05(s) and obtain τ < 0.0675(s) from Proposition 3.4 and the condition (21) in Theorem 3.9 with K = 3 * [1, 4,6,4] T , i. e., the agents (25) converge to a stationary consensus asymptotically (see Figure 5). To show the effect of introducing the delay-dependent compensation part, we consider the relationship between the communication delay and the compensating delay.…”

Consensus of Second Order Multi-Agent Systems with Exogenous Disturbance Generated by Unknown Exosystems

“…The consensus problem of multi-agent systems has received increasing attention in recent years due to its broad applications in such areas as cooperative control of unmanned aircrafts and underwater vehicles, flocking of mobile vehicles, communication among wireless sensor networks, rendezvous, formation control, and so on, see [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. In the past years, many researches have been firstly concerned with consensus problems of first order multi-agent systems [16][17][18][19][20].…”

Constrained consensus of asynchronous discrete-time multi-agent systems with time-varying topology

“…Thus, discrete-time multi-agent systems have found widely applications and their dynamics have attracted a lot of research interest [3][4][5]8,17,19,23,24,29,30], in which each agent synchronously receives it neighbors' information at discrete time instants, where the synchrony means that all agents update their states using the information of its neighboring agents at the same time. However, considering a central synchronizing clock may not be available and the communication topology is dynamically changing [25]. In [25], the authors studied the stationary consensus of asynchronous second-order multi-agent systems under switching topology, where asynchrony means that each agent's update action is independent of the others'.…”

“…However, considering a central synchronizing clock may not be available and the communication topology is dynamically changing [25]. In [25], the authors studied the stationary consensus of asynchronous second-order multi-agent systems under switching topology, where asynchrony means that each agent's update action is independent of the others'.…”