Sampled-Data Nonfragile Bipartite Tracking Consensus for Nonlinear Multiagent Systems: Dealing With Denial-of-Service Attacks

This paper is concerned with the sampled-data bipartite tracking consensus problem for a class of nonlinear multiagent systems (MASs) with input saturation. Both competitive and cooperative interactions coexist among agents in the concerned network. By resorting to Lyapunov stable theory and linear matrix inequality (LMI) technique, several criteria are obtained to ensure that the considered MASs can achieve the bipartite tracking consensus. Besides, with the help of the decoupled method, the dimensions of LMIs are reduced for mitigation of the computation complexity so that the obtained results can be applied to large-scaled MASs. Furthermore, the controller gain matrix is explicitly expressed in terms of solutions to a set of LMIs. We also provide with an estimate of elliptical attraction domain of bipartite tracking consensus. Finally, numerical simulation is exploited to support our theoretical analysis.

The consensus problem of nonlinear multi-agent systems is studied in this paper, considering the semi-Markov switching topologies under DoS (denial-of-service) attacks. In this regard, an event-triggered mechanism is introduced for multi-agent systems under DoS attacks. Moreover, combining the semi-Markov topology with the event-triggered mechanism, a new consensus controller under DoS attacks is proposed. Furthermore, by choosing the Lyapunov–Krasovskii function and applying the matrix inequality technique, a sufficient and necessary condition is derived for the system stability as well as the state consensus. Subsequently, H∞ norm is proposed to enhance the performance of the multi-agent systems. Finally, a numerical example is provided to show the effectiveness and applicability of the proposed approach.

The consensus issue for the nonlinear multiagent systems (MASs) with transmission delays subjected to deception attacks is addressed based on sampled-data control. Due to the universality of cyber attacks, this paper considers a kind of deception attacks which occur randomly at sampling instant and can modify the communication information. By employing the two-sided looped-functional method, an augmented Lyapunov-Krasovskii functional (LKF) is constructed to fully utilize the information on the sampling interval, which makes some free matrices be not necessarily positive definite. Then, the sufficient criteria are presented to ensure the consensus of MASs with deception attacks. Furthermore, the controller gain matrix and the maximal sampling interval are obtained based on the decoupled approach. Finally, the numerical example is exploited to verify the effectiveness of our results.

This paper investigates the bipartite leader-following consensus problem for multi-agent systems with nonlinear dynamics and multi-layer signed digraph topologies. According to the structural balance theory, some sufficient conditions are explored for reaching the bipartite leader-following consensus of the multi-layer signed networks by using the pinning control strategy, which are related to the dynamics of the network nodes and the topology of the multi-layer signed network. These conditions are also suitable for traditional single layer signed networks. The numerical example shows the correctness and effectiveness of the proposed method.

Secure consensus for PDEs-based multiagent systems under DoS attacks via boundary control approach

This paper investigates the event-triggered prescribed-time bipartite consensus of nonlinear multi-agent systems. In order to significantly reduce the communication burden and energy consumption, a novel event-triggered mechanism and triggering condition are proposed. Then, a distributed prescribed-time control protocol is proposed for the discussed nonlinear multi-agent systems to achieve bipartite consensus within the prescribed time based on the event-triggered mechanism. Using the Lyapunov stability theory, the stability of the nonlinear multi-agent systems is proved and the corresponding sufficient conditions are obtained. Moreover, it is shown that the Zeno behavior can be excluded. Simulation results are presented to show the effectiveness of the theoretical results.

consensus problem of multi agent systems catch great attention in recent years. It is mainly due to its vast applications. Designing an appropriate control protocol that guarantees the desired agreement between the agents is the main purpose of the consensus problem. A linear matrix inequality (LMI)-based approach for the H_∞ consensus of leader-follower nonlinear multi-agent system (MAS) is proposed in this paper. In the proposed framework, fuzzy Lyuponov function (FLF) is chosen. Some slack matrices are introduced to decouple the Lyapunov matrices from the systems' one which provide more degrees of freedom to the consensus problem and leads to decrease the conservativeness. As a result, sufficient conditions for consensus problem are presented in terms of LMIs. Finally, In order to evaluate the validity and effectiveness of the proposed approach, a numerical example for consensus of nonlinear MAS with thirteen followers is solved and simulation results are provided. Obtained results demonstrate the solid validity and great effectiveness of the proposed approach.

This paper considers event-triggered bipartite consensus issues for discrete-time nonlinear networked multi-agent systems with antagonistic interactions and denial-of-service (DoS) attacks. Firstly, a pseudo partial derivative technology is applied to obtain an equivalent dynamic linearization model of the controlled system. The signed graph theory is employed to analyze the coopetition relationships among agents. Next, a distributed combined measurement error function is formulated to transform the bipartite consensus issue into a consensus issue. Then, an output predictive compensation scheme is proposed to offset the influence of DoS attacks. Furthermore, a dead-zone operator is designed to improve the flexibility of the proposed event-triggered mechanism. Additionally, a data-driven event-triggered resilient bipartite consensus scheme is formulated. Then, the convergence of the proposed method is strictly proved by using the Lyapunov theory and the contraction mapping principle, which indicates that the bipartite consensus error could be cut to a small region around zero. Finally, hardware tasks are conducted to verify the effectiveness of the proposed method.

Distributed impulsive consensus of nonlinear multi-agent systems with input saturation

This article investigates the leader-following consensus problem of discrete-time nonlinear multiagent systems (MASs) over fading channels. With the consideration of the transmission among followers maybe affected by the fading networks, the nonidentical fading channels model is constructed. To reduce the transmission network burden, the dynamical event-triggered mechanism (DETM) is developed. Different from most of existing event-triggered strategies, the threshold parameter in the developed dynamical event-triggering condition is dynamically adjusted according to a dynamic rule. Based on the DETM, a distributed consensus control protocol is designed under fading channels. Then, sufficient criteria are provided to ensure that MASs can achieve the leaser-following consensus, and satisfy the H∞ performance index in the presence of fading channels. The desired controller parameters can be derived in terms of solutions of matrix inequalities that are lightly solvable. In the end, simulation results show that the designed dynamical event transmission policy is capable of diminishing communication burden more promptly and effectively than some existing ones.

This article studies the distributed adaptive failures compensation output-feedback consensus for a class of nonlinear multiagent systems (MASs) with multiactuator failures allowing unmatched redundancy under directed switching graphs. With estimated information of neighbors, a novel distributed reference generator is designed. To compensate the unmeasured state variables of each agent, a reduced-order dynamic gain filter is constructed. Based on the generator and filter, and using the recursive design method, a distributed adaptive protocol is designed, where the adaptive technique is used to compensate the actuator failures. The proposed scheme can significantly relax conditions on the communication graph, which allows the graph to be disconnected at any time instant. The number of introduced variables in the filter and its dimension is greatly reduced and, thus, reduces the numerical challenge. The output-feedback consensus for nonlinear MASs with actuator failures and possible unmatched actuator redundancy is addressed for the first time. The consensus error can converge to an arbitrarily small set not affected by actuator failures, and the resulting closed-loop system is semiglobally stable. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

Event-based leader–follower consensus of nonlinear multi-agent systems under denial-of-service

Adaptive observer-based bipartite tracking consensus for nonlinear multi-agent systems with unknown sensor failures.

Event-triggered bipartite consensus of second-order multi-agent systems under DoS attacks

This paper focuses on the consensus of multi-agent systems with unknown nonlinear dynamics under heterogenous topologies. The stability analysis is based on Lyapunov method and graph theory. Sufficient conditions in terms of linear matrix inequality (LMI) are given to guarantee the consensus of the multi-agent systems. The algorithms of none-zero velocity consensus and the zero velocity consensus are provided in this paper. We give two simulations at the end of this paper, showing the states of positions and velocities of all agents can reach consensus, under the proposed control laws.