Consensus Control For Multi-agent Systems Research Articles

Mean-square consensus control of multi-agent systems driven by fractional Brownian motion

Mean-square consensus control of multi-agent systems driven by fractional Brownian motion

Finite-Time Dynamic Event-Triggered Full-State Constraints Consensus Control for Multiagent Systems with Switching Topologies and Mismatched Disturbances

This paper investigates finite-time dynamic event-triggered full-state constraints consensus control for nonlinear multiagent systems with switching topologies and unknown disturbances. First, all the system states will not exceed the predefined range, which has guiding significance for the constraint control of velocity and position in multiagent systems. Second, to balance the control errors and event-triggered control, a novel finite-time dynamic event-triggered scheme is developed for multiagent systems, which can achieve fast convergence rates and save communication resources. Third, to improve the system performances, a finite-time command filter is designed to remove transient errors resulting from filtering errors and explosion of complexity. All closed-loop signals are proved to be bounded, and the tracking errors quickly converge into a narrow neighborhood of zero in finite-time. To sum up, the proposed control scheme balances the effects of unknown disturbances, unknown nonlinear dynamics, and limited communications bandwidth, which can improve the control performance for the multiagent systems under time-varying switching topologies. Finally, simulation results validate the suggested approach using a mechanical platform model.

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.

Consensus Control of Leader–Follower Multi-Agent Systems with Unknown Parameters and Its Circuit Implementation

With the development and progress of Internet and data technology, the consensus control of multi-agent systems has been an important topic in nonlinear science. How to effectively achieve the consensus of leader–follower multi-agent systems at a low cost is a difficult problem. This paper analyzes the consensus control of complex financial systems. Firstly, the dynamic characteristics of the financial system are analyzed by the equilibrium points, bifurcation diagrams, and Lyapunov exponent spectra. The behavior of the financial system is discussed by different parameter values. Secondly, according to the Lyapunov stability theorem, the consensus of master–slave systems is proposed by linear feedback control, wherein the controllers are simple and low cost. And an adaptive control method for the consensus of master–slave systems is investigated based on financial systems with unknown parameters. In theory, the consensus of the leader–follower multi-agent systems is proved by the parameter identification laws and linear feedback control method. Finally, the effectiveness and reliability of the consensus of leader–follower multi-agent systems are verified through the experimental simulation results and circuit implementation.

Output Consensus Control of Multi-Agent Systems With Switching Networks and Incomplete Leader Measurement

Output Consensus Control of Multi-Agent Systems With Switching Networks and Incomplete Leader Measurement

Event-Triggered Adaptive Preassigned Finite-Time Consensus Control for Multiagent Systems With Nonlinear Faults.

This article investigates a novel neuro-adaptive barrier Lyapunov function (BLF)-based event-triggered preassigned finite-time consensus control with asymptotic tracking for the nonlinear multiagent systems. The proposed approach is designed to broaden the scope of application by considering the high-order nonstrict-feedback dynamics of each agent with dynamic uncertainties subject to external disturbances and nonaffine nonlinear faults. A neural network (NN) is employed to approximate the unknown nonlinear terms. By fusing the NNs and Butterworth low-pass filter technique, the issues arising from the nonaffine nonlinear fault are addressed. To save the communication resources, a novel dynamic event-triggered mechanism based on an enhanced switching threshold is suggested. Additionally, a novel concept called the preassigned finite-time performance function (PFTPF) is defined to improve the transient and steady-state performances as well as providing faster response. The key feature of the proposed adaptive BLF-based control based on the bound estimation method is the introduction of a smooth function with decreasing variable which not only ensures that all the signals remain bounded and the synchronization errors are restricted within the PFTPF but also guarantees that the tracking errors asymptotically converge to zero. Finally, an illustrative example is provided to verify the feasibility of the proposed control approach.

PDE-Based Boundary Adaptive Consensus Control of Multiagent Systems With Input Constraints.

The leader-follower adaptive consensus control problem is addressed for partial differential equations (PDEs) multiagent systems (MASs), and these agents are composed of flexible manipulator systems with input nonlinearity, boundary uncertainties, and time-varying disturbances. Because of the spatial variables in the model, the design of adaptive protocols is more difficult than that of ordinary differential equation (ODE) MASs. By designing the Lyapunov function, a novel distributed boundary control (BC) protocol is constructed, which not only ensures the consensus of angular positions but also suppresses the boundary vibration of each agent. The hybrid effects of dead zones and input saturation on flexible manipulator systems are addressed using the approximation properties of neural networks (NNs). In addition, the disturbance adaptive laws are proposed to provide a control solution for bounded and time-varying disturbances. Furthermore, by applying the Lyapunov stability theory, the uniformly bounded stability of the multiflexible manipulator can be ensured. Finally, the feasibility of the presented control approach is verified using numerical examples.

Adaptive Consensus Control of Multiagent Systems With an Unstable High-Dimensional Leader and Switching Topologies

Adaptive Consensus Control of Multiagent Systems With an Unstable High-Dimensional Leader and Switching Topologies

Human-in-the-Loop Consensus Control for Multiagent Systems With External Disturbances.

In this article, the human-in-the-loop leader-follower consensus control problem is addressed for multiagent systems (MASs) with unknown external disturbances. A human operator is deployed to monitor the MASs' team by transmitting an execution signal to a nonautonomous leader in response to any hazard detected, with the control input of the leader unknown to all followers. For each follower, a full-order observer, in which the observer error dynamic system decouples the unknown disturbance input, is designed for asymptotic state estimation. Then, an interval observer is constructed for the consensus error dynamic system, where the unknown disturbances and control inputs of its neighbors and its disturbance are treated as unknown inputs (UIs). To process the UIs, a new asymptotic algebraic UI reconstruction (UIR) scheme is proposed based on the interval observer, and one of the significant features of the UIR is the capacity to decouple the control input of the follower. The subsequent human-in-the-loop asymptotic convergence consensus protocol is developed by applying an observer-based distributed control strategy. Finally, the proposed control scheme is validated through two simulation examples.

Edge-based event-triggered consensus control of multi-agent systems against DoS attacks

This article focuses on the security consensus control for general linear multi-agent systems against denial of service (DoS) attacks. In particular, an edge-based event-triggered protocol is proposed to reduce unnecessary information transmission through energy-limited and fragile networks, where the dynamic event-triggered condition is designed by introducing internal dynamic variables. The state of agents is dynamically estimated, and the control inputs based on estimated value can offer better control performance. It is demonstrated that under DoS attacks, the security consensus of multi-agent systems can be realised without Zeno behaviour by adopting the dynamic edge-based event-triggered control strategy. Finally, a numerical simulation example is included to prove the effectiveness of the proposed method.

Novel Dynamic Event-Triggered Consensus Control of Multiagent Systems With Markovian Switching Topologies Under DoS Attacks.

This article focuses on the issue of novel dynamic event-triggered consensus control of multiagent systems (MASs) with denial-of-service (DoS) attacks. Different from the conventional Markovian switching topologies, the generally uncertain semi-Markovian (GUSM) switching topologies with partially unknown elements and time-dependent uncertainties are constructed for the leader-following MASs by considering the equipment performance and external uncertain environment influence. To save communication resources, the novel dynamic memory event-triggered strategy (DMETS) is presented to decrease the frequency of communication between agents. Some secure consensus control criteria are established for the MASs with GUSM switching topologies and DoS attacks due to the potential system communication disruption caused by attackers. Finally, two physical system examples are designed to prove the effectiveness of the presented method.

Prescribed Time Fuzzy Adaptive Consensus Control for Multiagent Systems With Dead-Zone Input and Sensor Faults

Prescribed Time Fuzzy Adaptive Consensus Control for Multiagent Systems With Dead-Zone Input and Sensor Faults

Fully-distributed Consensus Control of Multi-agent Systems Under Stochastic Hybrid Attacks on a Directed Graph

Fully-distributed Consensus Control of Multi-agent Systems Under Stochastic Hybrid Attacks on a Directed Graph

Consensus Control of Multi-Agent System with Virtual Agents Considering Obstacle Avoidance

A multi-agent system (MAS) is a system whose overall behavior is determined by local interactions among multiple autonomous agents. Recently, research has been conducted on the application of MASs in real-world environments, in which the agents are assumed to be robots that drive on the ground, i.e., autonomous mobile robots, and acquire external environmental information using cameras. In such cases, the information that can be obtained by the agent is limited to the field of view (FOV) of the respective camera, and the overall graph structure is dynamic and time varying. In addition, because the FOV may be obstructed by obstacles during camera measurements, obstacle avoidance must be considered. In this study, we examined the MAS consensus problem considering the effects of a limited FOV obstructed by obstacles. Specifically, we propose a control method using virtual agents that considers obstacle avoidance based on funnel control. In addition, simulation study was performed to demonstrate the effectiveness of the proposed method for solving the MAS consensus problem in an environment with obstacles.

Adaptive expected-time tracking consensus control for multiagent systems with external disturbances and time delays

This paper studies the expected-time tracking control problem for multiagent systems with disturbances and time delays. The expected-time control scheme can ensure that control objectives can be completed within the desired time. In the other words, the output signal can track the reference signal in an expected time. Based on a special error and the adaptive technology, the expected-time tracking consensus control scheme is achieved. Moreover, by using the neural networks technique, the unknown nonlinear functions which often exist in the dynamic of the system are handled. According to the Lyapunov stability theorem and the Lyapunov–Krasovskii function, it is proved that the consensus errors are semi-globally uniformly ultimately bounded. At last, the feasibility of the control method is verified by a simulation example.

Guaranteed Performance Event-Triggered Adaptive Consensus Control for Multiagent Systems under Time-Varying Actuator Faults

A guaranteed performance event-triggered adaptive consensus control is established for uncertain multiagent systems under time-varying actuator faults. To eliminate the impact caused by actuator faults, an adaptive neural network compensation strategy is developed. Simultaneously, by implementing the asymmetric barrier Lyapunov function and transform function, a prescribed time consensus control with guaranteed performance, is constructed. Furthermore, to reduce the frequency of information transmission, an adjustable switching event-triggered control (ASETC) is proposed by using a modified hyperbolic tangent function. It combines the advantage of the relative threshold strategies and the characteristics of the hyperbolic tangent function, giving better flexibility in saving network resources and guaranteeing system performance. By applying the constructed control method, systems with prescribed performance consensus in a prescribed time are achievable while limited network resources and unknown time-varying faults are present. Some simulation examples implemented in MATLAB (R2022a) are given to demonstrate the above results.

Prescribed Time Consensus Control of Multiagent Systems With Minimized Time-Varying Cost Function

Prescribed Time Consensus Control of Multiagent Systems With Minimized Time-Varying Cost Function

Data-Based Optimal Consensus Control for Multiagent Systems With Time Delays: Using Prioritized Experience Replay

Data-Based Optimal Consensus Control for Multiagent Systems With Time Delays: Using Prioritized Experience Replay

Adaptive Optimal Consensus Control of Multiagent Systems With Unknown Dynamics and Disturbances via Reinforcement Learning

Adaptive Optimal Consensus Control of Multiagent Systems With Unknown Dynamics and Disturbances via Reinforcement Learning

Optimal Consensus Control for Multi-Agent Systems With Unknown Dynamics and States of Leader: A Distributed KREM Learning Method

Optimal Consensus Control for Multi-Agent Systems With Unknown Dynamics and States of Leader: A Distributed KREM Learning Method