Event-triggered Bipartite Consensus Research Articles

Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults

Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults

A Novel Event-Triggered Bipartite Consensus for PDE-Based Multiagent Systems With Switching Topologies and Antagonistic Interactions.

Unlike the traditional studies on multiagent systems (MASs), this article investigates a class of MASs with spatial properties, whose agents are modeled by partial differential equations (PDE), in addition, to make the model more comprehensive, the Markovian switching topology with partially unknown probability is taken into account. The purpose of this article is to achieve the bipartite consensus for the above PDE-based MASs. In fact, the consideration of spatial factors in MASs will exacerbate the network transmission pressure, to overcome this problem, a novel spatiotemporal event-triggered mechanism is developed. Compared with the existing event-triggered mechanism, the proposed one is not only time-dependent but also covers the influence of spatial variables on the trigger conditions, which helps to further reduce the triggering frequency. Finally, three examples are given to verify the validity of the conclusion we proposed.

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 Event-Triggered Bipartite Consensus for Nonlinear Multi-Agent Systems: Asymmetric Full-State Constraints

Observer-Based Event-Triggered Bipartite Consensus for Nonlinear Multi-Agent Systems: Asymmetric Full-State Constraints

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.

Hybrid Event-Triggered Bipartite Consensus Control of Multiagent Systems and Application to Satellite Formation

This work studies event-triggered bipartite consensus problem of multi-agent systems (MAS) with structurally balanced signed graph. A hybrid system approach is proposed to deal with the leaderless and leader-following bipartite consensus problems in a unified framework, and a novel hybrid event-triggering mechanism (ETM) is proposed to reduce the usage of communication resources. By appropriately defining closed-loop states, a unified hybrid model is constructed for both leaderless and leader-following MAS. Then, stability analysis and ETM design results are given under hybrid systems framework. It is worth noting that the designed hybrid ETM is in decentralized form rather than distributed form. Moreover, the lower bound of triggering intervals can be pre-selected, i.e., Zeno-freeness is guaranteed, that is important for control implementation. The proposed method is applied to satellite formation system in simulation results to show the effectiveness. <i>Note to Practitioners</i>&#x2014;This paper considers bipartite consensus control problem of MAS, which can be applied to some practical systems, e.g., bidirectional formation of unmanned air vehicles, since the control objective in these applications can be transformed into bipartite consensus control problem of MAS. Compared with the existing results, a hybrid system approach is proposed for consensus analysis of MAS with or without leader, and a novel event-triggering mechanism is proposed, which is more easier to be implemented, so, the proposed approach is more friendly for control engineers. The obtained results are applied to satellite formation control problem and the effectiveness is verified, and it is expected that the proposed approach can be extended to MAS with more realistic network-induced constraints and applied to more practical engineering systems.

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.

Event-triggered bipartite consensus for nonlinear multi-agent systems under switching topologies: A time-varying gain method

In this paper, the event-triggered bipartite consensus problem is investigated for nonlinear multi-agent systems under switching topologies, only part of topologies contain directed spanning tree rooted at the leader. First, a dynamic bipartite compensator is constructed based on relative output information to provide control signal. Then, the time-varying gain method is adopted to propose a compensator-based event-triggered control protocol without Zeno behavior. Notably, the control protocol proposed achieves the bipartite consensus while reducing update frequency effectively. Moreover, a low conservative switching law is designed by the topology-dependent average dwell time strategy, which fully considers the differences among topologies and provides an independent average dwell time for each topology. As an extension, the nonlinear multi-agent systems with non-zero input of leader are further studied. Finally, a practical example is presented to demonstrate the feasibility of proposed control protocol.

Observer-Based Dynamic Event-Triggered Bipartite Consensus of Discrete-Time Multi-Agent Systems

In this brief, the dynamic event-triggered bipartite consensus is explored for discrete-time multi-agent systems (MASs) under competitive network. Different from the existing works on dynamic event-triggered consensus of discrete-time MASs, observer based protocol is proposed by using the related output information. With the help of Lyapunov function method, some sufficient conditions are obtained and the control gains can be determined by solving discrete-time algebraic Riccati equations. Finally, a simulation example is presented to effectively verify the theoretical results.

Event-triggered bipartite consensus control algorithm design for nonlinear second-order multi-agent systems

Bipartite consensus of nonlinear second-order multi-agent systems with directed communication topology is investigated in this article. A kind of novel event-triggered control protocol is proposed, which based on relative information sensing. Different from some conventional event-triggered control for second-order multi-agent systems, the event-triggered control in distributed way for second-order multi-agent systems is studied in this article, which imply that the controller of each follower only needs to collect the local information. To eliminate too large control gain, the control gain of control protocol is further designed based on adaptive way. Moreover, these control algorithms prove that Zeno behavior can be avoided. Finally, the performance of the proposed control protocols is presented by virtue of two simulation examples.

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.

Event-Triggered Bipartite Consensus of Linear Multi-agent Systems Under DoS Attacks

Event-Triggered Bipartite Consensus of Linear Multi-agent Systems Under DoS Attacks

Event-Based Bipartite Consensus of Multi-Agent Systems Subject to DoS Attacks

This paper investigates the event-triggered bipartite consensus control of multi-agent systems subject to DoS attack. Existing results of relevant issues are usually confined by an implicit assumption that the real-time information of DoS attack is available for the construction of triggering strategy. However, some practical systems may not be equipped with elaborated attack detection mechanism, which means the trigger may not be notified the emission and suspension instants of attack timely. To settle with this scenario, we develop a novel distributed hybrid event-driven strategy which schedules the ordinary and attack-affected triggering laws by judging whether the previous transmission attempt of corresponding follower is successful, rather than utilizing detailed attack information directly. Furthermore, taking antagonistic interactions among agents into consideration, a resilient event-based control scheme is developed over signed digraph. Then, based on the analysis of hybrid Lyapunov functions exhibiting discontinuous property at practical triggering instants, a set of sufficient conditions which can ensure the exponential leader-following bipartite consensus of the investigated systems are presented. We also prove that Zeno behavior is excluded for triggering attempt sequences. Besides, the developed results are further extended to a self-triggered case. Finally, simulation results are provided to verify the effectiveness of the proposed control scheme.

Prescribed Performance Bipartite Consensus Control for Stochastic Nonlinear Multiagent Systems Under Event-Triggered Strategy.

In this article, the event-triggered bipartite consensus problem for stochastic nonlinear multiagent systems (MASs) with unknown dead-zone input under the prescribed performance is studied. To surmount the influence of the dead-zone input, the dead-zone model is transformed into a linear term and a disturbance term. Meanwhile, the prescribed tracking performance is realized by developing a speed function, which means that all tracking errors of MASs can converge to a predefined set in a given finite time. Moreover, the unknown nonlinear dynamics are approximated by fuzzy-logic systems. By combining the dynamic surface approach and the Lyapunov stability theory, we design an adaptive event-triggered control algorithm, such that the bipartite consensus problem of stochastic nonlinear MASs can be achieved, and all signals are semiglobally uniformly ultimately bounded in probability of the closed-loop systems. Finally, simulation examples are proposed to verify the feasibility of the algorithm.

Antagonistic Interactions-Based Adaptive Event-Triggered Bipartite Consensus Quantized Control for Stochastic Multiagent Systems

In a network of multiagent systems (MASs), the interaction between agents is not necessarily cooperative, but may be antagonistic, when the communication topology of a fixed spanning tree is formed. Although the cooperative control methods have been widely studied, the control methods aiming to the coexistence of antagonistic and cooperative interactions are rarely researched. Therefore, for antagonistic and cooperative interactions, this article addresses the bipartite cooperative quantized control problem for nonlinear stochastic MASs by using an event-triggered mechanism. The MASs model we chose allows cooperative and antagonistic interactions to coexist, with every agent being an independent individual. The Gaussian function is introduced to simulate cooperation and competition between two agents. Fuzzy neural networks are applied to approximate the unknown nonlinear functions, which reduces the burden of online calculation. Furthermore, to reduce the communication burden, an adaptive event-triggered approach with a varying threshold is developed. Meanwhile, according to sector bound property, a nonlinearity decomposition strategy of asymmetric hysteresis quantizer is applied. Compared with the previous situation that only event-triggered mechanism or quantizer is considered, this article reduces the communication burden to the greatest extent by codesigning the event-triggered mechanism and quantizer. Based on the backstepping technique, we propose a novel distributed adaptive control protocol, which not only achieves bipartite consensus control, but also guarantees that all the signals in the closed-loop system are bounded in probability, and the bipartite synchronization error converges to a small range near the origin. Finally, the performance of the proposed control strategy is illustrated through simulation.

Observer-Based Secure Event-Triggered Bipartite Consensus Control of Linear Multiagent Systems Subject to Denial-of-Service Attacks

This brief deals with the secure bipartite consensus problem for linear multi-agent systems (MASs) with Denial-of-Service (DoS) attacks subject to an observer-based dynamic event-triggered strategy (OBDES). Two event-triggered strategies involved with dynamic threshold are developed in controller and observer channels. Based on the connected structurally balanced signed graph, a new observer-based secure control protocol integrated of OBDES and relative output measurements of neighboring agents is proposed. The control strategy with dynamic coupling gains is fully distributed, which only requires to obtain the observer information from neighboring agents. Then, some criteria for secure bipartite consensus under DoS attacks are established. In addition, it is demonstrated that the Zeno behavior cannot not occur. At last, a numerical simulation is provided to verify the effectiveness of the proposed controller.

Dynamic event-triggered bipartite consensus for uncertain high-order nonlinear multi-agent systems

Dynamic event-triggered bipartite consensus for uncertain high-order nonlinear multi-agent systems

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

This paper is concerned with the secure bipartite consensus of second-order multi-agent systems under denial-of-service (DoS) attacks. The communication network is an antagonistic network, in which there is cooperative or competitive relationship between neighboring agents. Meanwhile, information cannot be transmitted when the system is attacked. A novel event-triggered control algorithm based on sampled data is proposed to save limited resources and exclude the Zeno behavior. By applying the convergence of monotone sequences, graph theory as well as the discrete-time Lyapunov function method, some sufficient conditions on threshold parameters, frequency and duration of DoS attacks, and sampling period are derived to ensure the bipartite consensus under DoS attacks. Finally, the correctness and advantages of theoretical results are demonstrated by a numerical simulation.

Event-Triggered Bipartite Consensus for Fuzzy Multiagent Systems Under Markovian Switching Signed Topology

In this article, we study the problems of bipartite and cooperative consensus with a strictly dissipative performance for fuzzy multiagent systems (MASs) in a unified framework. First, we prove that bipartite consensus over a structurally balanced signed graph is equivalent to cooperative consensus over the corresponding unsigned graph by leveraging the gauge transformation for a class of nonlinear MASs. Then, a polynomial fuzzy model is constructed to describe the nonlinear MAS formed by one leader and followers. For mitigating communication and computational load, a mode-dependent event-triggered transmission strategy is proposed. By establishing the switching topologies through Markovian process, a new sampled-data event-triggered consensus protocol is designed. With a mode-dependent Lyapunov–Krasovskii function, a novel relaxed dissipative criterion is obtained. The criterion guarantees that all agents can achieve both event-triggered cooperative consensus and event-triggered bipartite consensus with the same magnitude but opposite signs for MASs over structurally balanced signed directed graphs and Markovian switching topologies. Moreover, the event-triggered parameters and consensus control gains can be numerically solved via the sum-of-squares method. Simulation results are given to show the effectiveness of the proposed design 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.