Mathematical Problems in Engineering

Volume 2019, Article ID 4725418, 5 pages

https://doi.org/10.1155/2019/4725418

## Partial Component Consensus of Discrete-Time Multiagent Systems

^{1}College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050024, China^{2}Department of Mathematics, Luliang University, Lishi 033000, China^{3}College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China

Correspondence should be addressed to Gang Zhang; nc.ude.utbeh@gnahzgnag

Received 21 August 2018; Accepted 4 April 2019; Published 16 April 2019

Academic Editor: Zhiyun Lin

Copyright © 2019 Wenjun Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

The multiagent system has the advantages of simple structure, strong function, and cost saving, which has received wide attention from different fields. Consensus is the most basic problem in multiagent systems. In this paper, firstly, the problem of partial component consensus in the first-order linear discrete-time multiagent systems with the directed network topology is discussed. Via designing an appropriate pinning control protocol, the corresponding error system is analyzed by using the matrix theory and the partial stability theory. Secondly, a sufficient condition is given to realize partial component consensus in multiagent systems. Finally, the numerical simulations are given to illustrate the theoretical results.

#### 1. Introduction

In recent years, the theory of consistency, as the basis of coordinated control of multiagent system, has attracted extensive attention from many researchers [1–3]. The unified nature of multiagent systems is wildly applied to computing science [4], systems and control [5–7], and distributed sensor networks [8–10].

The consistency of the discrete multiagent systems is that the state of all agents in a discrete system model can achieve asymptotic convergence under certain conditions. Many researchers have discussed the consistency problem of multiagent systems [11–14] and have obtained a lot of research results. Xie Dongmei and Wang Shaokun considered the consensus of second-order discrete-time multiagent systems with fixed topology in [15]. In 2016, Gao Yulan et al. studied group consensus for second-order discrete-time multiagent systems with time-varying delays under switching topologies in [16]. At the same year, Cao Yanfen and Sun Yuangong discussed consensus of discrete-time third-order multiagent systems in directed networks in [17]. Furthermore, the consensus of leader-following multiagent has also received a lot of attention. Wang Yunpeng et al. proposed an algorithm to research the consensus of discrete-time linear multiagent systems with communication noises in [18]. Xu Xiaole et al. investigated the leader-following consensus problem of discrete-time multiagent systems through Lyapunov method in [19].

The consistency of discrete multiagent systems has more advantages than continuous multiagent systems. For example, it can reduce a lot of computation, and the speed of convergence is fast and so on. Therefore, the research of discrete consistency has some practical significance. Wu Binbin et al. have studied the partial component consensus of continuous multiagent systems in [20]. In this paper, we discuss the partial component consistency of discrete leader-following multiagent system. Based on the matrix theory and the partial stability theory, together with designing an appropriate pinning control protocol, a sufficient condition is proposed to realize partial component consensus in multiagent systems.

In detail, the remainder of this paper is organized as follows: Section 2 contains the problem statement and preliminaries; Section 3 presents the main result about the partial component consistency of discrete leader-following multiagent system; Section 4 provides a numerical example to verify the effectiveness of the proposed results; Section 5 offers concluding remarks.

#### 2. The Problem Statement and Preliminaries

In this section, we will give the basic concept of partial component consistency, basic matrix theory, and some definitions and lemmas. For details, refer to [20, 21].

We consider the following n-dimensional discrete system:where , , . Supposing , , and , , , .

Similar to the definition of partial component stability for continuous system in [21], we give the following definition of partial component stability for discrete system.

*Definition 1. *The trivial solution of (1) is stable for vector , if , and when , there must be .

*Definition 2. *The trivial solution of (1) is attracted to vector , if , , and when , there must be , where is the attraction area of the vector .

*Definition 3. *The trivial solution of (1) is asymptotically stable for vector , if it is stable and attracted for vector .

Lemma 4 (see [20]). *Let , then there exists a nN-order permutation matrix , where is the first kind of elementary row transformation matrix, such that the can hold, where is the Kronecker product.*

#### 3. Main Results

In this section, we consider a first-order discrete multiagent system, which consists of N following agents and a leader, and suppose the equation of state for the following agent iswhere, expresses the state of agent; is a diagonal matrix.

Supposing the dynamic equation of the leader agent iswhere is the state of leader agent.

Next we consider the problem of partial component conformance of discrete leader-following multiagent system under directed network topology. We design the controller as follows:where denotes coupling strength; is the intercoupling matrix; if the agent can receive the information from the agent, then ; otherwise, . If the agent can receive the information from the leader agent, then ; otherwise, .

Let satisfy and , and let . We can get the error system from (2), (3), and (4) as follows: We can write the above equation as a vector form:where , , , represents n-order identity matrix.

In order to discuss the asymptotic stability of the trivial solution of the error system (6), we try to do the following transformation. Let and , where is the elementary matrix in Lemma 4 and . We can get through calculation; in this case, (6) will change to the following equation: We can simplify the above equation,Next we give two useful definitions for this paper.

*Definition 5. *If there exist , such that the solution of system (2) and (3) satisfy , then system (2) and (3) achieve consensus for the first components.

*Definition 6. *If there exist , such that the solution of system (2) and (3) satisfy , then system (2) and (3) achieve consensus for the first component.

Theorem 7. *Let , for the control item, if there exist , such that system (2) and (3) satisfywhere is the element of the matrix , ; then, system (2) and (3) can achieve consensus for the first components.*

*Proof. *Define the following Lyapunov function candidate: where , . Similar to literature [19], we can obtain the following:In this case, if (9) can be held, then there exist , such thatTherefore,when , , i.e., . Therefore, ; then the solution of (8) is asymptotically stable for partial vector element; i.e., system (2) and (3) can achieve consensus for the first components.

#### 4. Numerical Examples

In this section, a numerical example has been given to show that our theoretical result obtained above is effective.

*Example 1. *Given the parameter and in system (2) as and , we consider the consensus of the discrete leader-following multiagent system for the first two components (i.e., ). Supposing the state of the agent (the subscript of the state of the leader denotes ) is , . Designing and as follows: then bring , , and into (4). Through simple calculations, at the same time, we set and ; then, (9) will be held. In this case, it is straightforward to check that all the conditions in Theorem 7 hold. Next we will give the topology diagram of agent connection and the error trajectories of system (2) and (3) through* Matlab* software.

Figure 1 expresses the topology connection of the given agent. Next we give the evolution diagram of the state error of the leader-following agent (Figure 2); Figures 2(a) and 2(b) represent the consensus of system (2) and (3) for the first two components and Figure 2(c) represents that system (2) and (3) cannot achieve consensus for the third component.