Cluster Consensus Of Multi-agent Systems Research Articles

Event-Triggered Cluster Consensus of Multi-Agent Systems via a Modified Genetic Algorithm.

This article is concerned with the event-triggered output feedback cluster consensus of leader-following multi-agent systems (MASs) under limited communication resources. Specifically, the distributed agents are divided into several clusters to accomplish different collective tasks under diverse intracluster and intercluster communications. First, to alleviate excessive communication resource consumption, two sampled-data-based event-triggered schemes are developed to distinguish agent-to-agent communications within clusters and between clusters. Based on these schemes, an event-based cluster consensus control protocol is proposed to solve the problem. Then, sufficient criteria on asymptotic stability of the resulting closed-loop system are derived and expressed in terms of matrix inequalities. It is noteworthy that the derived criteria for controller design are nonlinear and nonconvex with respect to the output feedback control gains and triggering parameters. To handle this issue, a modified genetic algorithm (MGA) with multiple subpopulations is proposed, where the subpopulations are independent of each other. The key feature of the designed MGA lies in that the fitness value is described as an accumulation of initial value and weighing value of each matrix inequality. Finally, an application of satellite formation flying is exemplified to demonstrate the effectiveness of the derived theoretical results.

Refined Dynamic Event-Triggering Cluster Consensus of Multiagent Systems With Fixed/Switching Topology.

This article is concerned with cluster consensus control of multiagent systems (MASs) with the fixed/switching topology under a dynamic event-trigger (DET) mechanism. A refined sampled-data-based DET scheme is proposed by introducing two dynamically adjusting threshold parameters to distinguish the different transmission requirements for neighboring agents intra and outer cluster. Faced with the difficulties of acquiring full state information among spatially distributed agents, output feedback is employed to construct cooperative control protocols. Both fixed and switching topologies are considered to execute the designed DET-based cooperative cluster consensus control protocols. By constructing appropriate Lyapunov-Krasovskii functionals (LKFs), some sufficient criteria in terms of matrix inequalities for the cluster consensus of MASs are derived, which can ensure that the error system with the proposed DET-based control strategy is asymptotically stable. Facing the nonconvex issue induced by output feedback, a particle swarm optimization (PSO)-based control design algorithm is novelly developed to calculate the control gains and event-triggering parameters jointly based on the derived stability criteria. The elements of the matrix variables are valued stochastically in certain ranges and the fitness function is designed as the accumulation of the weighting value of each matrix inequality. Finally, an application of multiple satellites formation flying is applied to numerically illustrate the effectiveness of the cluster consensus control strategy with the designed DET mechanism.

Distributed secure consensus for multiagent systems based on removing intra-cluster coupling restrictions and its application to energy systems

Cluster consensus of multiagent systems has provided analytical techniques for various industrial domains. As agents work in networked environments, their secure consensus control becomes essential desirable in response to cyber attacks. At that point, we investigate the secure cluster consensus in directed network systems under deception attacks and mixed delays. First, a control strategy for improving arbitrarily fixed topologies based on an extended state observer is proposed to ensure cluster consensus. In the framework of the proposed strategy, several criteria are derived to guarantee cluster consensus for agents. Second, different from the current works that require sufficiently strong intra-cluster coupling strength, the proposed consensus condition ensures fewer intra-cluster coupling restrictions. Third, the Halanay inequality is used to handle the mixed delays and reduce the parameters in the consensus criterion, which improves the efficiency of verifying the consensus. Finally, the simulation results on the IEEE 39-bus energy system are provided for validating the effectiveness of the proposed method, while achieving excellent tracking performance for the frequency and power deviations.

Leader-Following Cluster Consensus of Multiagent Systems With Measurement Noise and Weighted Cooperative–Competitive Networks

Leader-following cluster consensus is investigated for multiagent systems with weighted cooperative–competitive networks and measurement noise. A stochastic approximation protocol is proposed for interactively balanced and sub-balanced networks, and pinning control is introduced to deal with the divergence phenomenon in interactively unbalanced networks. With these protocols, sufficient conditions for reaching a strong mean-square leader-following cluster consensus are established for all the three types of networks, which are also extended to the cases without measurement noise. Numerical examples illustrate the effectiveness of the proposed protocols and theoretical analysis.

Cluster consensus of multi-agent systems with general linear and nonlinear dynamics via intermittent adaptive pinning control

This paper investigates the cluster consensus of multi-agent systems (MASs) with general linear and nonlinear dynamics via intermittent adaptive pinning control, where each cluster has a virtual leader whose state can be sensed by only a small part of followers on some disconnected time intervals because of communication constraints. The communication topology is considered to be weakly connected, that is, it is not necessary to be in-degree balanced, strongly connected or contain a directed spanning tree. To realise the cluster consensus, a class of intermittent adaptive pinning control protocols is proposed according to difference that the agents receive information source. The pinning gains are designed to be intermittent adaptive and with an exponential convergence rate, which will effectively reduce communication costs, avoid the pinning gains being larger than those needed in practice. Meanwhile, it guarantees that the pinning gains quickly converge to steady value. Correspondingly, some sufficient consensus criteria are derived to guarantee that the agents in the same cluster asymptotically can reach consensus while the agents in different clusters can reach different consensus. Rigorous proofs are given by the aid of Lyapunov stability theory and matrix theory. Finally, a numerical simulation example is presented to validate the main results.

Cluster Consensus of Multiagent Systems With Weighted Antagonistic Interactions.

This article addresses the problem of cluster consensus for multiagent systems (MASs) associated with weighted antagonistic interactions. Compared with some existing results, a general communication topology among agents is introduced in this article, where there is no need to confine directed cycles to the root of a spanning tree. By taking into consideration the structures of directed cycles and multiple paths, the judgment of structural balance is simplified significantly. A novel cluster consensus protocol is also proposed for structurally unbalanced digraphs. Moreover, two necessary and sufficient conditions are derived, by which cluster consensus can be achieved in an MAS if and only if its communication topology contains a directed spanning tree. Then, by employing an algebra theorem, a sufficient criterion for the unstable system under a directed cycle is obtained, whether the number of agents on this cycle is odd or even. Some illustrative examples are given to demonstrate the effectiveness of theoretical results.

Input Delay Effect on Cluster Consensus in Continuous-Time Networks

In this paper, we investigate the effect of input time-delay on the cluster consensus of multi-agent systems operating in continuous-time. Contrary to the studies on cluster/group consensus in the literature, the clusters are not pre-determined. We investigate the stability of a multi-agent network with fixed input time-delay The analysis yields the upper bound of time-delay that does not affect the number of clusters and convergence properties of the agents. Theoretical results are illustrated via several simulations.

Cluster Consensus in Discrete-Time Networks of Multiagents With Inter-Cluster Nonidentical Inputs

In this paper, cluster consensus of multiagent systems is studied via inter-cluster nonidentical inputs. Here, we consider general graph topologies, which might be time-varying. The cluster consensus is defined by two aspects: intracluster synchronization, the state at which differences between each pair of agents in the same cluster converge to zero, and inter-cluster separation, the state at which agents in different clusters are separated. For intra-cluster synchronization, the concepts and theories of consensus, including the spanning trees, scramblingness, infinite stochastic matrix product, and Hajnal inequality, are extended. As a result, it is proved that if the graph has cluster spanning trees and all vertices self-linked, then the static linear system can realize intra-cluster synchronization. For the time-varying coupling cases, it is proved that if there exists T > 0 such that the union graph across any T-length time interval has cluster spanning trees and all graphs has all vertices self-linked, then the time-varying linear system can also realize intra-cluster synchronization. Under the assumption of common inter-cluster influence, a sort of inter-cluster nonidentical inputs are utilized to realize inter-cluster separation, such that each agent in the same cluster receives the same inputs and agents in different clusters have different inputs. In addition, the boundedness of the infinite sum of the inputs can guarantee the boundedness of the trajectory. As an application, we employ a modified non-Bayesian social learning model to illustrate the effectiveness of our results.