Event-triggered Control For Multi-agent Systems Research Articles

Distributed Dynamic Event-Triggered Control for Multi-Agent Systems With Quantization Communication

Distributed Dynamic Event-Triggered Control for Multi-Agent Systems With Quantization Communication

Fixed-time adaptive event-triggered control for multiagent systems with full-state constraints

This paper investigates the fixed-time adaptive event-triggered control problem for a class of nonlinear multiagent systems with full-state constraints. The problem of full-state constraints is solved for multiagent systems by utilising a one-to-one nonlinear mapping. The design conditions of the controllers are more easily satisfied than the existing barrier Lyapunov functions strategy. A fixed-time adaptive control scheme is proposed for unconstrained systems that are converted from constrained systems. In contract with the existing finite-time control schemes that rely on the initial states, this restriction condition can be removed in this paper. An improved event-triggered mechanism with an adaptable switching threshold is designed to provide flexible switching between fixed threshold and variable threshold policies, resulting in reduced execution and sampling. It is proved via the Lyapunov stability method that all signals of the closed-loop systems are semi-global practical fixed-time stable. Finally, the effectiveness of the proposed control strategy is verified by some simulation results.

A Novel Dual-Phase Based Approach for Distributed Event-Triggered Control of Multiagent Systems With Guaranteed Performance.

This article presents a novel dual-phase based approach for distributed event-triggered control of uncertain Euler-Lagrange (EL) multiagent systems (MASs) with guaranteed performance under a directed topology. First, a fully distributed robust filter is designed to estimate the reference signal for each agent with guaranteed observation performance under continuous state feedback, which transforms the distributed event-triggered control problem into a centralized one for multiple single systems. Second, an event-triggered controller is constructed via intermittent state feedback, making the output of each agent follow the corresponding estimated signal with guaranteed tracking performance. The proposed co-design scheme is of relatively low complexity in structure and cheap in computation since a priori knowledge of system nonlinearities or estimation of their bounds is not required in building the control scheme, and yet neither approximating structures nor adaptive online updating algorithms are needed. It is shown that the output tracking error of each agent is ensured to shrink into a prescribed precision set at an arbitrarily assignable convergence rate, although the plant states and the actuation signal are triggered simultaneously. All the internal signals are uniformly bounded and the occurrence of Zeno behavior is precluded. The efficiency of the proposed method is verified via numerical simulation.

Fixed-time event-triggered control for multi-agent systems with input delay.

An in-depth study on the fixed-time event-triggered obstacle avoidance consensus control in heterogeneous USV-AUV systems with input delay and uncertain disturbances are conducted in this paper. When initial state of the system fails to achieve consensus, the desired heterogeneous USV-AUV formation can be achieved by fixed-time consensus control, within a fixed predetermined time, regardless of the initial states. Besides, an event-triggered communication strategy among the agents is introduced in the system, significantly reducing communication energy consumption. By employing the proposed control strategy, the Zeno behavior also can be avoided. Additionally, an obstacle avoidance control algorithm for the heterogeneous USV-AUV system based on improved artificial potential fields (IAPF) is designed, which helps in avoiding both static and dynamic obstacles. Compared to existing research, this algorithm reduces control input jitter, resulting in smoother obstacle avoidance paths. Through extensive simulation experiments and comparisons with other methods, effectiveness and superiority of the proposed algorithm is validated.

Secure Consensus of Multiagent Systems With DoS Attacks via Fully Distributed Dynamic Event-Triggered Control

This article investigates the secure consensus problem of general linear multiagent systems with denial-of-service (DoS) attacks. Owning to the existence of DoS attacks, it is challenging to investigate the event-triggered control of multiagent systems in a fully distributed manner. This article presents a novel dynamic event-triggered mechanism to alleviate the limited communication resources. Moreover, the designed mechanism is fully distributed and scalable owing to the introduction of some adaptive coupling weights. Since the DoS attacks have been considered in the event-triggered rule design, a novel adaptive parameter with an additional exponential term is adopted to deal with DoS attacks. The Lyapunov design also introduces such a term for the subsequent stability analysis. Sufficient conditions guaranteeing the asymptotic consensus of the studied system are developed in light of the controller’s parameters, duration, and frequency of the DoS attacks. Strict proof is provided to demonstrate that a secure consensus can be reached effectively under the proposed control mechanism. Furthermore, it is shown that the Zeno behavior can be excluded from the designed triggering mechanism. Finally, simulations on a multiagent system consisting of interconnected unmanned intelligent vehicles are conducted to verify the results.

Simplified ADP for Event-Triggered Control of Multiagent Systems Against FDI Attacks

In this article, an optimal control scheme against false data injection (FDI) attacks for multiagent systems with unavailable system states is presented. The output data that remains uncorrupted is extracted from a group of output measurements during FDI attacks using a secure preselector. Then, on the basis of the unattacked output data, a state observer is utilized to identify system states. By taking the communication overhead into account, an event-triggered mechanism is employed to alleviate communication burdens. The solution of the optimal control problem related to event-triggered Hamilton–Jacobi–Bellman (HJB) equations is obtained within a simplified adaptive dynamic programming (ADP) framework. The key point is that a single network is introduced to successfully avoid the problem of repeated approximations in traditional dual networks. Note that the weight vectors in the single critic network are adjusted through experience replay (ER), which helps to avoid the restrictive persistence of excitation (PE) conditions. It is strictly proven that all the signals in the closed-loop system are uniformly ultimately bounded, and the critic network weight can converge to optimal values. Simulation results illustrate the effectiveness of the control scheme.

Observer-Based Dynamic Event-Triggered Control for Multiagent Systems With Time-Varying Delay

This article is concerned with the dynamic event-triggered-based adaptive output-feedback tracking control problem of nonlinear multiagent systems with time-varying input delay. By utilizing the approximation capability of neural network (NN), a low-gain nonlinear observer is first established to estimate the immeasurable states. To mitigate the effect of time-varying input delay, an auxiliary system with communication information is designed to generate the compensation signals. Then, a distributed adaptive composite NN dynamic surface control (DSC) strategy is proposed to acquire the satisfactory tracking accuracy, where the filter errors are compensated by the introduced serial-parallel estimation model. Moreover, an effective switching dynamic event-triggered mechanism is developed to determine the communication instants and reduce the update frequency of the controller. It is proven that the consensus tracking error converges to a residual set of the origin. Finally, simulation results are presented to demonstrate the effectiveness of the proposed composite NN DSC scheme.

Dual periodic event-triggered control for multi-agent systems with input saturation

This paper is concerned with the periodic event-triggered consensus of multi-agent systems subject to input saturation. Due to the nonlinearity caused by the input saturation constraint, the accuracy of the event-triggered mechanism to screen data will be reduced. To deal with this problem, a novel dual periodic event-triggered mechanism is first proposed, in which a saturation-assisted periodic event-trigger and a complemental periodic event-trigger work synergistically to screen data more efficiently under the input saturation constraint. In addition, considering the various disturbances in the environment, a more general mixed H∞ and passive performance is introduced to describe the disturbance attenuation level. Based on the Lyapunov–Krasovskii functional, some less conservative consensus criteria are obtained for the multi-agent systems. In addition, under different input saturation constraints, the relationship between the disturbance attenuation level and the data transmission rate is explored. After that, a particle swarm optimization algorithm is a first attempt to estimate and enlarge the region of asymptotic consensus. Finally, an example is given to verify the effectiveness and superiority of our proposed method.

Distributed Event-Triggered Control for Multiagent Systems Under Denial-of-Service Attacked Topology: Secure Mode Strategy

In this article, the secure event-triggered control problem is investigated for multiagent systems (MASs) compromised by Denial-of-Service (DoS) attacks with multiple modes. With the rapid development of information technology, DoS attacks against communication topologies are more and more common in MASs with cyber-physical features. To actively reduce the influences caused by DoS attacks, a secure mode strategy is proposed to make agents switch into the secure mode when attacks occur. In this strategy, each agent accesses or terminates the secure mode with bounded time delays after DoS attacks begin or end. Based on the switched system theory, the secure mode strategy against DoS attacks is modeled as the asynchronous switching between agent models and topologies. Finally, we obtain the sufficient conditions on the frequency and duration of DoS attacks, under which the designed controller can guarantee the consensus of MASs. By practical examples, the MASs with the secure mode strategy are illustrated to have better attack-resistant effectiveness than the ones without the secure mode strategy.

Distributed event-triggered control for multiagent systems with non-continuous communication faults and dynamic uncertainties

Distributed event-triggered control for multiagent systems with non-continuous communication faults and dynamic uncertainties

Sampled-data-based Event-triggered Control for Multi-agent Systems under Antagonistic Interactions

Sampled-data-based Event-triggered Control for Multi-agent Systems under Antagonistic Interactions

Saturated Threshold Event-Triggered Control for Multiagent Systems Under Sensor Attacks and Its Application to UAVs

This paper investigates the secure consensus tracking problem for continuous-time nonlinear multiagent systems with sensor attacks. By designing a secure data selector, the unattacked output data is extracted from a group of output measurements under sparse sensor attacks. Then, by virtue of the obtained data and neural networks, a state observer is constructed to estimate the unavailable system states, where the convex combination theory is introduced to reduce the difficulty of solving observation gains. To utilize the limited communication resources reasonably, a novel saturated threshold event-triggered control strategy is proposed to reduce control updates, and then each update is encoded into a binary signal (0 or 1) to further reduce the occupation of communication bandwidth. The designed control scheme ensures that all closed-loop signals are semi-globally uniformly ultimately bounded, and its effectiveness is verified via a simulation of attitude control of unmanned aerial vehicles.

Adaptive dynamic event-triggered control for multi-agent systems with matched uncertainties under directed topologies

This paper deals with the consensus problem of linear multi-agent systems (MASs) with matched uncertainties on directed topologies via a dynamic event-triggered control. To reduce the redundant communication, a distributed dynamic event-triggered (DET) protocol with a dynamic threshold is proposed, which makes the average time interval of controller update have a positive lower bound. The Zeno behavior can also be excluded. Furthermore, to avoid the assuming availability of full state information, an observer-based adaptive dynamic event-triggered (ADET) protocol is introduced. The proposed adaptive σ-modification technique for the time-varying coupling gain can render smaller control gain and achieve better regulatory effects. Compared with the existing DET scheme, the dynamic threshold with a positive lower bound can reach consensus with larger inter-execution times and less communication energy among agents. By using the Riccati equation and inequality techniques, some simple and convenient sufficient conditions are derived to guarantee the stability of the closed-loop system. Finally, two numerical examples are given to verify the effectiveness of the obtained theoretical results.

Event-Triggered Control for Multi-Agent Systems: Event Mechanisms for Information Transmission and Controller Update

Event-Triggered Control for Multi-Agent Systems: Event Mechanisms for Information Transmission and Controller Update

Event-Triggered Control for Multiagent Systems With Sensor Faults and Input Saturation

An adaptive neural network (NN) event-triggered control scheme is proposed for nonlinear nonstrict-feedback multiagent systems (MASs) against input saturation, unknown disturbance, and sensor faults. Mean-value theorem and Nussbaum-type function are invoked to transform the structure of the input saturation and overcome the difficulty of unknown control directions, respectively. On the basis of the universal approximation property of NNs, a nonlinear disturbance observer is designed to estimate the unknown compounded disturbance composed of external disturbance and the residual term of input saturation. According to the measurement error defined by control signal, an event-triggered mechanism is developed to save network transmission resource and reduce the number of controller update. Then, an adaptive NN compensation control approach is proposed to tackle the problem of sensor faults via the dynamic surface control (DSC) technique. It is proved that all signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results demonstrate the effectiveness of the presented control strategy.

Fully distributed dynamic event-triggered control for multi-agent systems with input saturation and actuator failure

This paper investigates the fully distributed dynamic event-triggered consensus problem for multi-agent systems with input saturation and actuator failure. Firstly, a distributed adaptive parameter is designed to estimate communication noise. Then, under the assumption that each agent is asymptotically null controllable with bounded controls, a low-gain state feedback control protocol is designed according to the algebraic Riccati equation. Furthermore, by introducing an internal dynamic variable, a novel fully distributed dynamic event-triggered control mechanism is proposed for multi-agent systems. Under this fully distributed dynamic event-triggered control mechanism, all agents of multi-agent systems can reach semi-global consensus and the Zeno behavior is excluded. Finally, a simulation example is presented to illustrate the effectiveness of the proposed algorithm.

Distributed event-triggered control for multi-agent systems under intermittently random denial-of-service attacks

This paper considers the event-triggered consensus problem for multi-agent systems (MASs) under intermittently random denial-of-service (IRDoS) attacks. The IRDoS attack compromises communication networks when the attacker is at active periods. Then, the distributed event-triggered controller is designed to achieve the consensus objective, and each agent’s communications towards neighbors are interrupted by the IRDoS attack with a certain probability when the triggered instants are at active periods of attackers. Furthermore, the sufficient conditions on the attack duration and successful probability, under which the designed control protocol guarantees secure consensus of MASs, are proposed. Finally, the effectiveness of the distributed event-triggered controller under a class of IRDoS attack is illustrated with a numerical example.

Integral-based event-triggered control for multi-agent systems with general linear dynamics

ABSTRACTThis paper proposes an integral-based event-triggered control strategy to solve the consensus problem of multi-agent systems with general linear dynamics. We first consider the leader-following consensus problem where the communication topology has a directed spanning tree with the leader as the root. It is proved that under the proposed strategy leader-following consensus is guaranteed and the inter-event intervals are lower bounded by positive constants. Then, the leaderless consensus problem of multi-agent systems is investigated under directed topology. We show that consensus is achieved and no Zeno behaviour occurs. Simulation results verify the effectiveness of the obtained results.

Event-triggered control for multi-agent systems

Event-triggered control for multi-agent systems

Event-Triggered Control of Multiagent Systems for Fixed and Time-Varying Network Topologies

A decentralized controller that uses event-triggered communication scheduling is developed for the leader-follower consensus problem under fixed and switching communication topologies. To eliminate continuous interagent communication, state estimates of neighboring agents are designed for control feedback and are updated via communication to reset growing estimate errors. The communication times are based on an event-triggered approach and are adapted based on the trade-off between the control system performance and the desire to minimize the amount of communication. An important aspect of the developed event trigger strategy is that communication is not required to determine when a state update is needed. Since the control strategy produces switched dynamics, analysis is provided to show that Zeno behavior is avoided by developing a positive constant lower bound on the minimum inter-event interval. A Lyapunov-based convergence analysis is also provided to indicate bounded convergence of the developed control methodology.