Multiconsensus of Second-Order Multiagent Systems with Input Delays

The multiconsensus problem of double-integrator dynamic multiagent systems has been investigated. Firstly, the dynamic multiconsensus, the static multiconsensus, and the periodic multiconsensus are considered as three cases of multiconsensus, respectively, in which the final multiconsensus convergence states are established by using matrix analysis. Secondly, as for the multiagent system with input delays, the maximal allowable upper bound of the delays is obtained by employing Hopf bifurcation of delayed networks theory. Finally, simulation results are presented to verify the theoretical analysis.


Introduction
Recently, distributed coordination control of multiagent systems has drawn an increasing attention of researchers.This is mainly due to the fact that its broad applications have ranged from cooperative control of unmanned air vehicles, formation control of mobile robots, and design of sensor network to swarm-based computing.The main objective of the consensus problem, which is one of the most fundamental issues in coordination control, is to design an appropriate control protocol to make a group of agents reach an agreement on certain quantities of interest by negotiating with their neighbors.
As we all know, the earlier study on consensus problem is primarily about single-integrator dynamic multiagent systems [1][2][3][4][5][6].In this case, the task of the consensus algorithm is to guarantee that positions of all the agents converge to a constant value.Moreover, the consensus problem of doubleintegrator dynamic multiagent systems has also aroused growing concern [7][8][9][10], which is more challenging than the first case.It is worth to point out that the control goal of all the aforementioned studies is to drive the states of all the agents in a network to a consistent value.
However, in reality, sometimes the agreements are different because of the changes of environment, situation, or cooperative tasks.For example, in nature, a flock of foraging birds may incorporate or evolve into different subgroups for the sake of resisting foreign intrusion.In the study of formation control problem, the formation is split into several subformations in order to fulfill total task or avoid obstacles, which results in different agreements.Hence, it is of vital significant to study multiconsensus and to design algorithms so that the agents in each subnetwork achieve consensus while there is no consensus among different subnetworks.To illustrate, by using pinning control technology, the multiconsensus problem of multiagent systems was investigated in [11,12], where the pinned agents were chosen in accordance with the topological structure of the underlying graphs.The multiconsensus of first-order multiagent systems was discussed under fixed topology and switching topology, in which the interaction between the two subnetworks was assumed to be balanced [13,14].Under the same assumptions, two different kinds of multiconsensus protocols of second-order multiagent systems for networks with fixed communication topology were presented [15].Under more mild assumptions, the authors proposed necessary and sufficient conditions of group consensus of first-order multiagent systems with directed and fixed topology [16].Inspired by the progress in the field, this paper tries to further investigate multiconsensus problem and propose a more general control protocol for second-order multiagent systems.

Mathematical Problems in Engineering
In addition, we found that time delay is inevitable in consensus convergence of multiagent systems.This is because both the movements of the agents and the congestion of the communication and connected controllers by networks may cause time delay.Hence, it is necessary to consider the effect of the time delay.Based on the frequency domain analysis, the consensus of first-order discrete-time multiagent systems with diverse input and communication delays was discussed in [17], which showed that the consensus condition was dependent on input delays but independent of communication delays.The leader following consensus problem with diverse input delays and symmetric coupling weights was explored [18].Besides, the consensus of heterogeneous multiagent systems with symmetric coupling weights under identical input delays and different input delays was analyzed in [19], respectively.The finite-time consensus problem of multiagent systems with delays was studied, in which the nonsmooth protocol was proposed to make the system reach agreement in finite time [20].So far, few works have been performed on multiconsensus of second-order multiagent systems with input delays.
Motivated by all the above results, we focus on the multiconsensus of second-order multiagent systems without delay and with delays, respectively.The network is divided into multiple subnetworks, and all the agents in it are divided into multiple groups consequently.We assume that information exchange exists between not only two agents in a group but also in different groups.Based on stability theory, three sorts of multiconsensus, namely, the dynamic multiconsensus, the static multiconsensus, and the periodic multiconsensus, are considered, in which the final multiconsensus convergence states are obtained for the case without delay.As for the case with input delays, we establish a sufficient condition by employing Hopf bifurcation of delayed networks theory, in which multiconsensus can be achieved if the time delay is less than a certain critical value.
The remainder of this paper is shown as follows.In Section 2, we present some concepts in graph theory and formulate the model to be studied.In Section 3, the multiconsensus problem of second-order multiagent system without delay and with input delays is discussed for the directed network, respectively.Meanwhile, the simulation results are presented to illustrate the effectiveness of the theoretical results in Section 4. Finally, we draw the conclusion in Section 5.
Notation.Throughout this paper, we let  be the set of real number.1  is denoted as an -dimensional column with all the elements being one and 0  is denoted as an -dimensional column with all the elements being zero.0 × denotes the  ×  matrix with all zero entries and   denotes  ×  identity matrix.Re() and Im() denote the real part and imaginary part of a complex number , respectively.det() denotes determinant of matrix .

Preliminaries and Problem Formulation
Let G = (V, , A) be a weighted directed graph with the vertex set V = {] 1 , ] 2 , . . ., ]  }, the edge set  ⊆ V × V, and a nonsymmetric matrix A = (  ) × .An edge   = (]  , ]  ) means that agent  can receive information from agent .A = (  ) × is defined as   ̸ = 0 if   ∈  and   = 0, otherwise.Moreover, we assume that   = 0 for all .The set of neighbors of agent  is denoted by In this paper, we consider a complex network (G, ) consisting of + agents.All the agents are divided into two parts and the agents in each part build up a subnetwork.Therefore, it consists of two subnetworks (G 1 ,  1 ) and (G 2 ,  2 ).We denote  1 = {1, 2, . . ., },  2 = { + 1, . . .,  + }, and  =  1 ∪  2 .Furthermore, we denote Consider vehicles with double-integrator dynamics given by where   ∈ , V  ∈  is the state and the velocity of the agent , respectively, and   ∈  is the control input.
Definition 1.For second-order multiagent system (1), three sorts of multiconsensus are defined.
(i) The system (1) is said to reach a dynamic multiconsensus asymptotically, if for any initial conditions, we have lim (ii) The system (1) is said to reach a static multiconsensus asymptotically if, for any initial conditions, we have lim  → ∞        () −   ()      = 0, ∀,  ∈   ,  = 1, 2, (iii) The system (1) is said to reach a periodic multiconsensus asymptotically if, for any initial conditions, all the agents in the same subnetwork can reach periodic consensus and the agents in different subnetwork can not coincide.
Remark 2. Obviously, the protocol (4) is a more general case, which contains protocol (3) in [9] as a special case.The consensus is achieved by designing protocol (3) in [9].But our idea is to establish criteria, which can make the first  agents reach a consistent state while the last  agents reach another consistent state.Therefore, the protocol (4) is proposed.(1) with protocol (4) can be written as follows: where  = [  ] is defined as Before moving on, we make the following assumption as in [12,13]: Assumption 3 means that the effect between two subnetworks is balanced.As a result, each row sum of the matrix  is zero.Therefore, 0 is an eigenvalue of .

Main Results
In this section, we deal with multiconsensus problem of second-order multiagent system (1).

Multiconsensus of Second-Order Multiagent System.
For the linear model ( 5), eigenvalues of matrix Γ are discussed first because they count a lot in stability analysis.Suppose that   ( = 1, . . .,  + ,  = 1, 2) and   are eigenvalues of Γ and −, respectively.
Let  be an eigenvalue of matrix Γ.Then, we have det Hence, Lemma 4 (see [15]).Under Assumption 3,  has a zero eigenvalue whose geometric multiplicity is at least two.
Proof.It is easy to verify that  1 = (1   , 0   )  and  2 = (0   , 1   )  are two linearly independent right eigenvectors of matrix  associated with zero eigenvalues.This completes the proof.
Note that Thus, It follows from (12) that  1 = (  1 ,  Denote It can be verified that  1 = ( Let  be the Jordan canonical form associated with Γ.Then, there exists a nonsingular matrix  such that where  1 is the Jordan upper diagonal block matrix corresponding to the eigenvalues   ( = 3, . . .,  + ;  = 1, 2).
For  > 0, one has   1  → 0 ( → ∞).Then, it follows from (19) that   → 0 and V  → 0 for all  ∈  as  → ∞.Remark 6.In Theorem 5, we mainly analyze the eigenvectors and generalized eigenvectors of matrix Γ associated with eigenvalues  1 and  2 .Then, we obtain the ultimate consensus state based on matrix theory.Lemma 7 (see [9]).Assume that Re() < 0,  0 ≥ 0, and  ≥ 0, the two roots of the polynomial By Theorem 5, it is easy to get the conclusion.

Corollary 9.
For  =  = 0,  0 > 0, and  1 > 0, suppose that − has two simple zero eigenvalues and all the other eigenvalues have negative real parts, second-order dynamic multiconsensus of system (1) can be achieved if where   are the nonzero eigenvalues of −.In addition, if the second-order dynamic multiconsensus is reached, one has which is consistent with the results of Theorem 1 in [16].For the special case of  = 0,  1 = 0,  0 = 1, and  > 0, one obtains a sufficient condition from Corollary 10: which is consistent with Theorem 3 in [16].Therefore, the case in [16] can be seen as a special case, and Theorem 8 presents more general results for multiconsensus of secondorder multiagent systems in this paper.
Corollary 12.For  = 0 and  > 0, if − has two simple zero eigenvalues and all the other eigenvalues have negative real parts, system (1) achieves periodic multiconsensus if where   are the nonzero eigenvalues of −.In addition, if the second-order periodic multiconsensus is reached, one can obtain as  → ∞, where  1 = (  11 ,   12 )  and  2 = (  21 ,   22 )  are the two linearly independent left eigenvectors of matrix  associated with zero eigenvalues which satisfy   1  1 = 1 and   2  2 = 1.
Proof.Since − has two simple zero eigenvalues and all the other eigenvalues have negative real parts and inequality (24) holds, it follows from Theorem 8 that the second-order consensus can be achieved in system (32) when  = 0, where all the roots of ∏ + =3   () = ∏ + =3 { 2 + ( −  1   ) + ( −  1   )} = 0 have negative real parts and the roots    of  2 +  +  = 0 ( ≥ 0,  ≥ 0) are located in the closed left-half plane.It means that all the roots of () = 0 are located in the closed left-half plane when  = 0.When  varies from 0 to  0 , by Lemmas 15 and 16, a purely imaginary root emerges and the sum of order of zero of () on the open right-half plane can change.Therefore, the stability of system (32) is not satisfied and multiconsensus cannot be achieved when  ≥  0 .
Remark 18.The idea of delays has been inspired by the idea used in [8,21,22].Consensus problem for double-integrator multiagent systems under delays has been also investigated in [8,22], where the input delays were regarded as bifurcation parameters.It can be seen that Hopf bifurcation occurs when time delays pass through some critical values where the conditions for local asymptotical stability of the equilibrium are not satisfied.

Simulation
In this section, we present numerical simulations to illustrate the effectiveness of the proposed theoretical analysis.
Let  =  = 0 and  0 = 1; from Corollary 9, it can be found that the dynamic multiconsensus can be

Figure 1 :
Figure 1: Topology graph of a network with seven agents.

Figure 2 :
Figure 2: Position and velocity states of agents in a network, where  1 = 0.48 and  1 = 0.49.

Figure 3 :Figure 4 :
Figure 3: Position and velocity states of agents in a network, where  = 0.68 and  = 0.66.

Figure 6 :
Figure 6: Position and velocity states of agents in a network with input delays, where  = 0.20 and  = 0.21.

Figure 7 :
Figure 7: Position and velocity states of agents in a network with input delays, where  = 0.27 and  = 0.28.