Consensus Of Multi-agent Systems Research Articles

Finite-Time Partial Component Consensus for Nonlinear Leader-Following Multi-Agent Systems

The problem of finite-time partial component consensus (FTPCC) for first-order nonlinear multi-agent systems (MASs) is investigated in this paper for the first time. By incorporating the permutation matrix approach, we derive a novel error system for identical components, which facilitates stability analysis. Leveraging partial variable stability theory and related foundational knowledge, we devise two adaptable protocols. These protocols are tailored to achieve FTPCC in nonlinear MASs, one for systems without disturbances and another for those with bounded disturbances. To validate our findings, numerical examples are provided, demonstrating the effectiveness of the proposed results.

Feedforward compensator based fuzzy adaptive asymptotic consensus for nonlinear multiagent systems

Feedforward compensator based fuzzy adaptive asymptotic consensus for nonlinear multiagent systems

Double adaptive event-triggered strategy for leader-following group consensus of heterogeneous multi-agent systems in cooperative–competitive networks

This article investigates adaptive event-triggered control for leader-following group consensus of hybrid heterogeneous multi-agent systems (HMASs) composed of single- and double-integrator agents under cooperative–competitive relationships. By using fully distributed control protocol and adaptive protocol, the leader-following group consensus can be achieved without global information. Additionally, a novel adaptive double dynamic event-triggered mechanism (DDETM) is proposed, in which two independent adaptive event-triggered conditions are devised to maintain events of communication and updates of controllers. Furthermore, adaptive parameters and internal dynamic variables are employed to reduce the number of triggers and exclude Zeno phenomenon. By utilizing Lyapunov stability theory, some sufficient conditions are acquired for the leader-following group consensus of the HMASs. Finally, simulation examples are given to prove the effectiveness of the proposed method.

Nodal Consensus in Multiagent Systems With Edge Communications

Nodal Consensus in Multiagent Systems With Edge Communications

Adaptive finite-time consensus tracking for nonlinear second-order multi-agent systems based on integral sliding mode

This paper delves into the investigation of finite-time consensus for second-order nonlinear multi-agent systems (MASs) with external disturbances under directed topology. The MASs considered in this study consist of n followers and a leader, all of which are subject to bounded disturbances. First, a continuous nonsingular integral terminal sliding mode is designed, which can effectively eliminate the singularity and chattering. Then, a finite-time disturbance observer is introduced to estimate and compensate for disturbances. Subsequently, an integral sliding mode adaptive controller is designed to enhance system’s robustness, improve response speed, and increase tracking accuracy. Furthermore, Lyapunov theory is utilized to demonstrate that the system achieves finite-time consensus under a directed connected topology. Finally, we apply a simulation to verify the efficacy of the proposed consensus control protocol.

Securing Consensus in Fractional-Order Multi-Agent Systems: Algebraic Approaches Against Byzantine Attacks

This paper investigates the behavior of fractional-order nonlinear multi-agent systems subjected to Byzantine assaults, specifically focusing on the manipulations of both sensors and actuators. We employ weighted graphs, both directed and undirected, to illustrate the system's topology. Our methodology combines algebraic graph theory with fractional-order Lyapunov techniques to develop algebraic requirements for leader-following consensus, providing a robust framework for analyzing consensus dynamics in these complex systems. We present quantitative results demonstrating the effectiveness of our approach, including two numerical examples that validate the proposed requirements for consensus evaluation. Notably, our work highlights the novelty of using fractional-order systems to enhance resilience against adversarial conditions, contributing significantly to the field of multi-agent systems. By clarifying key terms and streamlining our language, we ensure accessibility for a broader audience while emphasizing the implications of our findings for real-world applications.

Effect of dwell time on consensus in multiagent systems with time‐varying topologies

AbstractThis paper studies the effect of dwell time on consensus of high‐order multiagent systems with time‐varying topologies. In contrast to existing literature that only focuses on the convergence of consensus, the proposed work focuses on the sensitivity of consensus on the dwell time and studies its relationship with consensus behaviors. In particular, it is shown that dwell time determines the duration of agent interactions, resulting in different state dynamics, consensus values, and convergence speeds under different switching topologies. Such effects can impact the dynamical performance of the multiagent systems. To quantitatively analyze the effect, a procedure is proposed to estimate the consensus values with respect to the dwell time and switching topologies, and a condition is obtained to find the topologies that can speed up the convergence. The proposed study is applied to the regulation of microgrids, which proves to be effective in improving the performance and efficiency of controllers.

Distributed leader-following bipartite consensus for one-sided Lipschitz multi-agent systems via dual-terminal event-triggered mechanism

This article analyses leader-following bipartite consensus for one-sided Lipschitz multi-agent systems by dual-terminal event-triggered output feedback control approach. A distributed observer is designed to estimate unknown system states by employing relative output information at triggering time instants, and then an event-triggered output feedback controller is proposed. Dual-terminal dynamic event-triggered mechanisms are proposed in sensor–observer channel and controller–actuator channel, which can save communication resources to a great extent, and the Zeno behavior is ruled out. A new generalized one-sided Lipschitz condition is proposed to handle the nonlinear term and achieve bipartite consensus. Some stability conditions are presented to guarantee leader-following bipartite consensus. Finally, one-link robot manipulator systems are introduced to demonstrate the availability of the designed scheme. The results demonstrate that the agents of the robot manipulators can track the reference trajectories bi-directionally, and effectively reduce communication resources by 61.22% and 68.04% at the sensor–observer and controller–actuator channels, respectively.

Finite-Time Pinning Event-Triggered Control for Bipartite Consensus of Hybrid-Order Heterogeneous Multi-Agent Systems with Antagonistic Links

Finite-Time Pinning Event-Triggered Control for Bipartite Consensus of Hybrid-Order Heterogeneous Multi-Agent Systems with Antagonistic Links

Event-driven predefined-time practical consensus for multi-agent systems

Event-driven predefined-time practical consensus for multi-agent systems

Resilient consensus of heterogeneous multi-agent systems under asynchronous optimal DoS attack schedules

This study aims to address the challenge of achieving resilient consensus in heterogeneous multi-agent systems (MASs) under asynchronous optimal Denial of Service (DoS) attack schedules. Considering the start and duration of adversaries vary from different communication channels of MASs, we mainly focus on how adversaries with limited energy choose channels to launch attacks to cause the greatest damage to system performance. Based on dynamic programming, an asynchronous optimal DoS attack schedules generation algorithm is obtained. Optimal DoS attack schedules provides a basis for designing more effective secure control methods. Then, a distributed resilient control strategy that utilizes an observer-based approach to achieve output consensus in heterogeneous MASs under asynchronous optimal DoS attack schedules is proposed. Additionally, we establish conditions regarding the durations and frequencies of DoS attacks as well. Finally, two simulations are performed to showcase the efficacy of our proposed method.

Distributed Bipartite Consensus of Multi-Agent Systems via Disturbance Rejection Control Strategy

This work aims to focus on analyzing the consensus control problem in cooperative–competitive networks in the occurrence of external disturbances. The primary motive of this work is to employ the equivalent input-disturbance estimation technique to compensate for the impact of external disturbances in the considered multi-agent system. In particular, a suitable low-pass filter is implemented to enhance the accuracy of disturbance estimation performance. In addition, a specific signed, connected, and structurally balanced undirected communication graph with positive and negative edge weights is considered to express the cooperation–competition communication among neighboring agents. The cooperative–competitive multi-agent system reaches its final state with same magnitude and in opposite direction under the considered structurally balanced graph. By utilizing the properties of Lyapunov stability theory and graph theory, the adequate conditions assuring the bipartite consensus of the examined multi-agent system are established as linear matrix inequalities. An illustrative example is delivered at the end to check the efficacy of the designed control scheme.

Consensus for discrete-time second-order multi-agent systems in the presence of noises and semi-Markovian switching topologies

In this paper, we focus on the control problem of mean square consensus for second-order continuous-time multi-agent systems with multiplicative noises under Markovian switching topologies. A new Lyapunov function based on the Laplacian matrix of the corresponding union topology of all possible topologies is designed for the stochastic stability analysis of consensus. Applying matrix theory and stochastic stability for stochastic differential equations, we can analyze the consensus problem of the considered systems with the designed Lyapunov function. In addition, we present the sufficient conditions of the mean square consensus exponentially for the considered stochastic systems. Finally, we give an simulation example to numerically validate our theoretical results.

Min–max group consensus of discrete-time multi-agent systems under directed random networks

This paper studies the min–max group consensus of discrete-time multi-agent systems under a directed random graph, where the presence of each directed edge is randomly determined by a probability and independent of the presence of other edges. Firstly, we propose a min–max consensus protocol without memory, and give the necessary and sufficient conditions to ensure that the multi-agent system can achieve the min–max group consensus in the sense of almost sure and mean square, respectively. Secondly, we design a novel consensus protocol with memory and a behavior mechanism. Using the stochastic analysis theory and the extremal algebra, some necessary and sufficient conditions are obtained for achieving the min–max group consensus in the sense of almost sure and mean square, respectively. It is shown that the protocol with memory can solve the loss problem of the maximum and minimum initial states. Finally, the effectiveness of the two group consensus protocols and the behavior mechanism is verified by four numerical simulations.

Leader-Following Sampled-Data Consensus of Multiagent Systems With Successive Packet Losses and Stochastic Sampling.

In practical applications, sampled-data systems are often affected by unforeseen physical constraints that cause the sampling interval to deviate from the expected value and fluctuate according to a certain probability distribution. This probability distribution can be determined in advance through statistical analysis. Taking into account this stochastic sampling interval, this article focuses on addressing the leader-following sampled-data consensus problem for linear multiagent systems (MASs) with successive packet losses. First, the relationship of the equivalent sampling interval between two successive update instants is established, taking into account the double randomness introduced by both SPLs and stochastic sampling. Then, the equivalent discrete-time MAS is obtained, and the overall leader-following consensus problem is formulated as a stochastic stability problem of the equivalent system by incorporating the sampled-data consensus protocol and properties of the Laplacian matrix. Based on the equivalent the discrete-time system, a consensus criterion is derived under a directed graph by using the Lyapunov theory and leveraging a vectorization technique. By the introduction of a matrix reconstruction approach, the mathematical expectation of a product of three matrices, including the system matrix and its transpose, can be determined. Then, the consensus protocol gain is designed. Finally, an example is provided to validate our theoretical results.

Distributed adaptive secure consensus control for multiagent systems under denial-of-service attacks

This paper investigates the security consensus of multiagent systems (MASs) under denial-of-service (DoS) attacks. First, we introduce a novel dynamic consensus protocol against DoS attacks by utilising relative measurement outputs. Then, based on the edge pinning technique, the novel distributed synchronous adaptive laws are designed to tune a small fraction of coupling strengths between neighbouring agents, under which all updating of coupling strengths will stop when DoS attacks are activated. To extend the application of secure dynamic edge pinning consensus scheme, we further develop the distributed asynchronous adaptive laws, under which only the coupling strengths of the attacked edges stop updating rather than all coupling strengths when DoS attacks are activated. Note that the proposed secure dynamic edge pinning consensus protocols with distributed synchronous and asynchronous adaptive laws are fully distributed and operate independently of any global information. At last, we validate the validity of the proposed distributed adaptive secure dynamic consensus schemes via an example.

Adaptive predefined-time consensus for nonlinear multi-agent systems with input delay and performance constraints

This paper investigates the predefined-time tracking consensus issue for a class of non strict-feedback nonlinear multi-agent systems (MASs) under input delay and error performance constraints by adaptive backstepping control strategy. Firstly, the impact of input delay is eliminated by Pade approximation. With the help of an intermediate state variable, the considered MASs with input delay are revised as the independent-delay systems. Secondly, under constrained distributed error and corrected nth virtual error, the ln-type barrier Lyapunov function (BLF) is adopted to solve the error performance constrains and reduce the complexity of differentiation. Meanwhile, an adaptive predefined-time controller is designed to realize the tracking purpose by backstepping method and radial basis function neural networks (RBFNNs) approximation. Finally, a numerical simulation example and a practical application are presented to test the effectiveness for the proposed control strategy.

Dynamic event-triggered consensus for stochastic delay multi-agent systems under directed topology

This paper addresses the mean-square exponential consensus (MSEC) challenge in stochastic delay multi-agent systems (MASs) under directed topology. The main contributions include avoiding infinitely fast sampling and conducting a random stability analysis. First, a dynamic event-triggered mechanism (DETM) with a fixed positive lower bound for the inter-execution time is designed to prohibit Zeno behavior. The proposed control strategy does not involve the expectations of system signals. Then, sampling errors are estimated using Itô isometry, which ensures that the fixed control at each work interval is maintained with adequate feedback capacity to mitigate the effects of these errors. Furthermore, with the help of a Halanay inequality in integral form and Lyapunov theorem framework, some conditions are proposed to guarantee the consensus of stochastic delay MASs under directed topology. Finally, an example is presented to prove the effectiveness of the DETM method.

A Novel Parallel Control Method for Optimal Consensus of Nonlinear Multiagent Systems.

This work concentrates on the initial introduction of parallel control to investigate an optimal consensus control strategy for continuous-time nonlinear multiagent systems (MASs) via adaptive dynamic programming (ADP). First, the control input is integrated into the feedback system for parallel control, facilitating an augmented system's optimal consensus control with an appropriate augmented performance index function to be established, which is identical to the original system's suboptimal control with a conventional performance index. Second, the feasibility of the proposed control scheme is evaluated based on the policy iteration algorithm, and the convergence of the algorithm is demonstrated. Then, an online learning algorithm becomes available to implement the ADP-based optimal parallel consensus control protocol without prior knowledge of the system. The Lyapunov approach is employed to indicate that the signals are convergent. Ultimately, the experimental data support the theoretical results.

Bipartite Fixed-time Output Consensus of Singular Heterogeneous Linear Multi-agent Systems Under Directed Signed Topology

Bipartite Fixed-time Output Consensus of Singular Heterogeneous Linear Multi-agent Systems Under Directed Signed Topology