Bipartite Consensus Of Multi-agent Systems Research Articles

Adaptive Critic Learning-Based Optimal Bipartite Consensus for Multiagent Systems With Prescribed Performance.

Developing a distributed bipartite optimal consensus scheme while ensuring user-predefined performance is essential in practical applications. Existing approaches to this problem typically require a complex controller structure due to adopting an identifier-actor-critic framework and prescribed performance cannot be guaranteed. In this work, an adaptive critic learning (ACL)-based optimal bipartite consensus scheme is developed to bridge the gap. A newly designed error scaling function, which defines the user-predefined settling time and steady accuracy without relying on the initial conditions, is then integrated into a cost function. The backstepping framework combines the ACL and integral reinforcement learning (IRL) algorithm to develop the adaptive optimal bipartite consensus scheme, which contributes a critic-only controller structure by removing the identifier and actor networks in the existing methods. The adaptive law of the critic network is derived by the gradient descent algorithm and experience replay to minimize the IRL-based residual error. It is shown that a compute-saving learning mechanism can achieve the optimal consensus, and the error variables of the closed-loop system are uniformly ultimately bounded (UUB). Besides, in any bounded initial condition, the evolution of bipartite consensus is limited to a user-prescribed boundary under bounded initial conditions. The illustrative simulation results validate the efficacy of the approach.

Bipartite Consensus of Multi-Agent Systems With a Non-Autonomous Leader Under Directed Switching Signed Graphs

Bipartite Consensus of Multi-Agent Systems With a Non-Autonomous Leader Under Directed Switching Signed Graphs

Adaptive Bipartite Consensus of Multi-agent Systems with Parameter Uncertainty and Leader of Nonzero Input under Signed Digraph

This article investigates the bipartite consensus problem for a class of multi-agent systems (MASs) with parameter uncertainty and leader of nonzero input under a signed digraph. Due to the unknown and time-varying input signal of the leader, followers are unable to obtain accurate information about the leader. For this purpose, a distributed adaptive observer is designed based on parameterization theory. Then, considering the existence of parameter uncertainty in the MASs, an auxiliary function is designed to compensate for the impact of uncertainty. Afterwards, an adaptive controller with dynamic coupling gain is designed based on observation errors and auxiliary function. Subsequently, it is demonstrated that the MASs with parameter uncertainty and leader of nonzero input can achieve bipartite consensus by stability analysis. Finally, the effectiveness of the proposed scheme is verified through simulation.

Event‐triggered bipartite consensus for multiagent systems with general linear dynamics: An integral‐type event‐triggered control

AbstractWe fill a gap in the proofs in the previous works (Wu X, Mu, X. Int J. Robust Nonlin Control. 2020;30:3753Ű3772; Zhang Z, Lunze J, Wang L. Int J Control. 2020;93:1005‐1014; Zhang Z, Wang L. J Robust Nonlin Control. 2018;28:4175Ű4187; Dai, M‐Z, Zhang C, Leung H, Dong P, Li B. IEEE Trans Syst, Man, Cybern: Syst. doi:10.1109/TSMC.2021.3119670) for the consensus using the integral‐based event‐triggered controls. More precisely, it was inferred for a Lyapunov function that is uniformly bounded by showing that is uniformly bounded for . However, this argument may fail without further information while the boundedness of is crucially used for applying Barbalat's lemma. The consequence of Barbalat's lemma is that which corresponds to the desired consensus result. To overcome this gap, Ma and Zhao (Inform Sci. 2018;457‐458:208‐221) put an extra condition about the boundedness of measurement error functions inside the proposed integral‐based event‐triggering protocol. In this article, we propose a new integral‐based event‐triggering protocol for bipartite consensus problems of the multi‐agent systems whose dynamics are described by general linear systems without adding the uniform boundedness of measurement error functions as (Ma Y, Zhao J. Inform Sci. 2018;457‐458:208‐221) did. Via our new integral‐based integral control strategy, we prove that the system achieves the bipartite consensus in asymptotic regime, and provide a complete solution of the freeness of both chattering and genuinely Zeno behaviors. Numerical results are provided supporting the effectiveness of the proposed controller.

Finite-Time Asymmetric Bipartite Consensus for Multi-Agent Systems Using Data-Driven Iterative Learning Control

Finite-Time Asymmetric Bipartite Consensus for Multi-Agent Systems Using Data-Driven Iterative Learning Control

Event-Triggered Bipartite Consensus of Multiagent Systems With Input Saturation and DoS Attacks Over Weighted Directed Networks

Event-Triggered Bipartite Consensus of Multiagent Systems With Input Saturation and DoS Attacks Over Weighted Directed Networks

Observer-Based Asynchronous Event-Triggered Bipartite Consensus of Multiagent Systems Under False Data Injection Attacks

This paper investigates bipartite consensus of multi-agent systems under unknown false data injection attacks. Attacks are launched in the channels from the controller to the actuator. To compensate the impact of attacks, an extended observer including the absolute output information is firstly constructed, and then an observer-based event-triggered controller is designed to save resources. Moreover, an observer-based fully asynchronous event-triggered controller is proposed to further reduce the communication cost. Sufficient criteria are deduced to guarantee bipartite consensus and Zeno behavior is further ruled out. Finally, numerical examples are given to illustrate the effectiveness of the derived results.

Bipartite consensus of multi-agent systems with matched uncertainty via fully distributed edge-based event-triggered mechanism

The leader-following bipartite consensus of multi-agent systems (MASs) with matched uncertainty is investigated by using the fully distributed asynchronous edge-based event-triggered mechanism. Firstly, event-triggered mechanisms are constructed for each edge and the leader to decrease the consumption of system resources. The state feedback and output feedback control protocols are proposed, which do not depend on the global values of the communication graph. Secondly, sufficient conditions for the bipartite consensus of MASs are obtained by Lyapunov stability theory. Thirdly, the feasibility of the proposed event-triggered mechanisms is further verified by exclusion of Zeno phenomenon. Finally, the effectiveness of control protocol is illustrated by simulation.

Distributed global adaptive bipartite consensus of multi-agent systems with signed communication topology structure

This paper focuses on designing a fully distributed adaptive fuzzy bipartite consensus control protocol for unknown nonlinear multi-agent systems with a class of undirected signed graph. Utilizing the fuzzy logical system universal approximator as a compensator to describe the uncertain nonlinear dynamics, a fully distributed adaptive fuzzy control protocol is proposed by means of re-parameterized approach and bounding technique, the global bipartite consensus of leader-following multi-agent systems without using any dynamics of the leader is proven via constructing a new Lyapunov function. The proposed protocol overcomes the drawback of the semi-global consensus in existing literature. Furthermore, as an extension of the former result, a bipartite formation control problem is also solved. Finally, the proposed methods are validated by simulation examples.

Leaderless and Leader-Following Bipartite Consensus of Multiagent Systems With Sampled and Delayed Information.

This article proposes a hybrid systems approach to address the sampled-data leaderless and leader-following bipartite consensus problems of multiagent systems (MAS) with communication delays. First, distributed asynchronous sampled-data bipartite consensus protocols are proposed based on estimators. Then, by introducing appropriate intermediate variables and internal auxiliary variables, a unified hybrid model, consisting of flow dynamics and jump dynamics, is constructed to describe the closed-loop dynamics of both leaderless and leader-following MAS. Based on this model, the leaderless and leader-following bipartite consensus is equivalent to stability of a hybrid system, and Lyapunov-based stability results are then developed under hybrid systems framework. With the proposed method, explicit upper bounds of sampling periods and communication delays can be calculated. Finally, simulation examples are given to show the effectiveness.

Distributed Event-Triggered Bipartite Consensus for Multiagent Systems Against Injection Attacks

This article studies fully distributed data-driven problems for nonlinear discrete-time multiagent systems (MASs) with fixed and switching topologies preventing injection attacks. We first develop an enhanced compact form dynamic linearization model by applying the designed distributed bipartite combined measurement error function of the MASs. Then, a fully distributed event-triggered bipartite consensus (DETBC) framework is designed, where the dynamics information of MASs is no longer needed. Meanwhile, the restriction of the topology of the proposed DETBC method is further relieved. To prevent the MASs from injection attacks, neural network based detection and compensation schemes are developed. Rigorous convergence proof that the bipartite consensus error is ultimately bounded is presented. Finally, the effectiveness of the designed method is verified through simulations and experiments.

Practical bipartite consensus for multi-agent systems: A barrier function-based adaptive sliding-mode control approach

This paper is concerned with bipartite consensus tracking for multi-agent systems with unknown disturbances. A barrier function-based adaptive sliding-mode control (SMC) approach is proposed such that the bipartite steady-state error is converged to a predefined region of zero in finite time. Specifically, based on an error auxiliary taking neighboring antagonistic interactions into account, an SMC law is designed with an adaptive gain. The gain can switch to a positive semi-definite barrier function to ensure that the error auxiliary is constrained to a predefined neighborhood of zero, which in turn guarantees practical bipartite consensus tracking. A distinguished feature of the proposed controller is its independence on the bound of disturbances, while the input chattering phenomenon is alleviated. Finally, a numerical example is provided to verify the effectiveness of the proposed controller.

Data-Driven Event-Triggered Bipartite Consensus for Multi-Agent Systems Preventing DoS Attacks

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.

Dynamic Event-Triggered Bipartite Consensus of Multiagent Systems With Estimator and Cooperative-Competitive Interactions

In this brief, the bipartite consensus problem of linear multi-agent systems with a dynamic event-triggered protocol is studied. A distributed controller with a cooperative-competitive mechanism and estimated states is first designed, and a dynamic event-triggered mechanism proposed in which the triggering threshold is dynamically updated by the designed auxiliary equation. Under this control strategy, the systems only need the states of the agent and neighboring agents at the triggering instants. At the same time, the estimator is considered to reduce the states deviation of multi-agent systems between adjacent triggering instants. Moreover, bipartite consensus can be achieved without Zeno behavior. Finally, the feasibility of the proposed method is illustrated in a unicycle model.

Asymmetric Bipartite Consensus of Multi-Agent Systems under Periodic Detection Event-Triggered Mechanism

This paper investigates the periodic event-triggered asymmetric bipartite consensus problem of multi-agent systems (MASs) under structurally balanced undirected signed graphs. In order to reduce the consumption of communication resources and continuous detection in the control process of MASs, a novel periodic detection event-triggered asymmetric bipartite consensus control protocol is proposed. In particular, each agent samples only in a fixed period. For each agent, two event conditions are given, and only when state error satisfies this event condition can the event be triggered. A new type of Laplacian matrix is constructed to achieve asymmetric bipartite consensus. The control method can guarantee the performance of MASs and have less communication resources. Based on the Lyapunov stability theorem and algebraic graph theory, the proposed periodic event-triggered control strategy is able to implement the asymmetric bipartite consensus when the topology is structurally balanced undirected signed graphs. The proposed method in this paper can reduce the restriction on the sampling period and automatically exclude Zeno behavior. Finally, the validity of the conclusion is verified by numerical simulation.

Event-triggered privacy-preserving bipartite consensus for multi-agent systems based on encryption

In this paper, the privacy-preserving-based bipartite consensus control problem is investigated for a class of discrete-time nonlinear multi-agent systems (MASs). The classical bipartite consensus control implementation relies on the explicit information exchange between agents, which will lead to the possible leakage of agents’ private information, especially the initial states. Therefore, to prevent data disclosure to neighbors inside the MASs and the outside eavesdroppers, the data is encrypted by means of Paillier encryption scheme during information transmission. This means each agent first sends the relative data in the form of ciphertext to its neighbors for further encryption process, and then restores the control protocol based on the returned encrypted information from the neighbors. Since homomorphic encryption only works for integers, the data must be quantized before encryption, and it will inevitably result in the quantization error. On the other hand, for the purpose of saving communication resources, both decentralized and distributed event-triggered schemes are also proposed. Resorting to the Lyapunov stability theory and algebraic graph theory, sufficient conditions are derived ensuring that the MASs subject to a confidential communication agreement can achieve the bounded bipartite consensus. Two numerical examples are presented to verify the validity of the theoretical results.

Resilient fixed-time bipartite consensus of multi-agent systems with nonlinear dynamics and directed graphs

This article is concerned with the bipartite fixed-time consensus problem for a class of multi-agent systems with nonlinear dynamics and directed graphs. To achieve the fixed-time consensus, a discontinuous control protocol is proposed. Compared to the protocols with undirected graphs, the control parameters are designed using a new Laplacian matrix based on an underlying undirected graph. Besides, to apply the method to the multi-agent systems with malicious agents, the proposed controller is combined with the Weighted Mean Subsequence Reduced (WMSR) algorithm which is modified for signed graphs. Finally, some simulations are presented to demonstrate the performance of the proposed method.

Distributed bipartite consensus for multi-agent systems with dynamic event-triggered mechanism

This paper address the distributed bipartite consensus problem of multi-agent systems (MASs) under undirected and directed topologies with dynamic event-triggered (DET) mechanism. The relationship among agents not only collaborative interaction but also competitive interaction are taken into account. A novel DET control protocol is raised with internal dynamic variables to guarantee that each agent can reach the bipartite consensus. Compared with the existing static triggering laws, the introduced DET strategy can significantly enlarge the interval time between two triggering instants. In addition, continuous information transmission in either controller updating or between agent and its neighbors is not demanded, which implies that the communication frequency can be extremely decreased. It is also proven that Zeno behavior does not occur. Finally, two numerical examples verify the validity of the presented theoretical results.

Event-triggered bipartite consensus of multi-agent systems in signed networks

<abstract><p>This paper focuses on the event-triggered bipartite consensus of multi-agent systems in signed networks, where the dynamics of each agent is assumed to be Lur'e system, and both the cooperative interaction and antagonistic interaction are allowed among neighbor agents. A novel event-triggered communication scheme is presented to save limited network resources, and distributed bipartite control techniques are raised to address the bipartite leaderless consensus and bipartite leader-following consensus respectively. By virtue of the Lyapunov stability theory and algebraic graph theory, bipartite consensus conditions are derived, which can be easily solved by MATLAB. In addition, the upper bounds of the sampling period and triggered parameter can be estimated. Finally, two examples are employed to show the validity and advantage of the proposed transmission scheme.</p></abstract>

H-infinity bipartite consensus of multi-agent systems with external disturbance and probabilistic actuator faults in signed networks

<abstract><p>The H-infinity bipartite consensus problem is addressed for a class of linear multi-agent systems with external disturbance, where the positive and negative links are allowed in communication topology. A novel event-triggered communication scheme is presented to save limited network resources, which dependents on information from neighboring agents at event-triggered instants, the given event-triggered condition is detected only at discrete sampling times, thus Zeno behavior can be excluded, two types of event-triggered matrices have been introduced in our event-triggered communication scheme, which can further reduce the sampled-data transmission compared with some existed results. Considering the probabilistic actuator faults, the reliable controller is designed based on sampled-data, then a new distribution-based fault model is constructed by using coordinate transform. Some H-infinity bipartite consensus criteria can be derived by the Lyapunov stability theory and algebraic graph theory, at the same time, the feedback matrices and event-triggered matrices can be obtained by solving some linear matrix inequalities. Finally, a numerical example is employed to show the validity and advantage of the proposed transmission scheme.</p></abstract>