Consensus of Heterogeneous Multi-Agent Systems Under Directed Topology

Abstract

In this paper, the consensus problem of heterogeneous multi-agent systems under directed topology is investigated. Specifically, this system is composed of three classes of agents respectively described by first-order, second-order and third-order integrator dynamics. By the aid of linear filter, graph theory and matrix theory, the consensus problem is realized based on the two proposed consensus protocols. Moreover, group consensus can also be solved by adjusting parameters. Finally, some examples were presented to illustrate the theoretical results. Our study is expected to establish a more realistic model and provide a method to solve the consensus problem of heterogeneous multi-agent systems in more complex situations.INDEX TERMS Consensus, directed topology, multi-agent systems, heterogeneous, linear filter.

Finite-Time Consensus of Heterogeneous Unmanned Aerial Agents in Network with Fixed and Switching Topology

“…This ensures that the real MASs will have identical performances as the reference model. To meet the objective in (22), we define the sliding surface by…”

“…In other works, [20], [21] the problem of heterogeneous consensus is addressed for first order and second order integrator agents with un-directed communication topology. Geng et al [22] includes third order integrator dynamics under directed communication network. However, most consensus algorithms based on this technique only assure asymptotic consensus amongst the agents.…”

Some Properties of Stochastic Matrices and Non-Homogeneous Markov Chains Generated by Nonlinearities in the Resource Network Model

“…In addition to describing physical diffusion processes in networks, similar models appear when simulating information processes, in particular the dynamics of opinions and reaching a consensus in multi-agent systems. At the present time, the classic DeGroot model [17] has many different modifications [18][19][20][21]. Homogeneous and non-homogeneous Markov chains are one of the main tools for describing multi-state systems, processes, and devices [22,23].…”

“…On the graph, it can be seen how the resource flows from the transient component to the vertices of the final component. (21). W = 14, and the vector of the initial state is Q(0) = (5, 4, 3, 2, 0, 0, 0, 0, 0).…”

“…Figure 3. The resource distribution over time for the network represented by matrix(21). W = 14, and the vector of the initial state is Q(0) = (5, 4, 3, 2, 0, 0, 0, 0, 0).…”