Consensus Of Multi-agent Systems Research Articles

Consensus of Discrete-Time Multiagent Systems With Transient Performance Constraints

Consensus of Discrete-Time Multiagent Systems With Transient Performance Constraints

Exponential Stability and H ∞ Performance of Uncertain Discrete-Time Switched Impulsive Systems: Applications to the Consensus of Multiagent Systems

Exponential Stability and <i>H</i> _∞ Performance of Uncertain Discrete-Time Switched Impulsive Systems: Applications to the Consensus of Multiagent Systems

Event-Based Reset Control for Consensus of Multiagent Systems Under Denial-of-Service Attacks: An Appointed-Time-Observer-Based Approach

Event-Based Reset Control for Consensus of Multiagent Systems Under Denial-of-Service Attacks: An Appointed-Time-Observer-Based Approach

Quantization-Based Adaptive Fuzzy Consensus for Multiagent Systems Under Sensor Deception Attacks: A Novel Compensation Mechanism.

This study mainly investigates the adaptive leader-following consensus tracking control problem for a class of nonlinear multiagent systems (MASs) subjected to unknown control directions, external disturbances, and sensor deception attacks. To start with, an equivalent MAS with known control directions is obtained by introducing a linear state transformation. For the purpose of estimating the unavailable system states caused by malicious attacks, a quantization-based fuzzy state observer is designed, and the fuzzy-logic system (FLS) is utilized to approximate nonlinear functions. Moreover, a dynamic uniform quantizer with scaling function is established to reduce information transmission. With the help of coordinate transformation and available compromised states, a novel compensation mechanism is designed to offset the influence of filter errors while avoiding the problem of "explosion of complexity" in the backstepping design process. In addition, the Nussbaum-type function is considered to eliminate the design obstacle of unknown control gains resulting from the attacks. Under the constructed consensus protocol, it is proved theoretically that the consensus tracking error converges to an adjustable small neighborhood of the origin, and all signals in the closed-loop system are bounded. Finally, the feasibility of the provided secure control scheme is verified through two simulation examples.

Fully distributed practical fixed-time fault-tolerant consensus of nonlinear multiagent systems

In this article, the practical fixed-time fault-tolerant consensus problem of a class of first-order nonlinear multiagent systems with actuator faults is investigated. Owing to the existence of uncertain actuator failures (multiplicative faults and additive faults) and non-linearities, it is challenging to study the fixed-time consensus problem of such multiagent systems in a fully distributed approach. To get over this challenge, a fully distributed adaptive protocol that utilizes adaptive techniques is proposed. Under this control protocol, multiagent systems can achieve consensus, and by adjusting controller parameters, the consensus error can converge to the acceptable bounded region in a fixed time. In addition, due to the introduction of adaptive parameters, the design of the control protocol is not dependent on any global network topology information, which means the control protocol is fully distributed. Therefore, the proposed scheme has better scalability and wider applicability. Finally, the simulation results are proposed to validate the fault-tolerant ability and fully distributed characteristics of the presented scheme.

Fixed-time consensus and finite-time flocking of second-order nonlinear multi-agent systems under false data injection attacks

This paper focuses on addressing consensus and flocking issues in second-order nonlinear multi-agent systems (MASs) under the false data injection attacks. Novel adaptive control protocols are proposed to effectively mitigate the impact of these attacks by updating adaptive parameters. Based on algebraic graph theory, matrix theory and the Lyapunov approach, various sufficient conditions are established, which show the fixed-time consensus and finite-time flocking can be achieved for the MASs. Moreover, some upper bounds for the settling time are derived in terms of the parameters of the model. Finally, three simulation examples are presented to validate the efficacy of our proposed theoretical results.

Event-triggered design for optimal output consensus of high-order multi-agent systems

In this paper, we study the optimal output consensus problem for networked linear multi-agent systems. Existing distributed algorithms usually rely on continuous communication among neighbouring agents or continuous update of each agent's local controller. To save communication and computation resources, we apply event-triggered technique to this optimal output consensus problem. We first constructively develop an event-triggered algorithm with a set of applicable parameters relying on event-triggered communication and control and show its effectiveness in solving the problem by rigorous proofs. Then we extend it to the case where the triggering conditions only have to be checked in some sampling time instants. Two simulation examples are given to illustrate the efficacy of our designs.

Mean Square Consensus of Multi-Agent Systems Over Non-Identical Delayed and Fading Channels

Mean Square Consensus of Multi-Agent Systems Over Non-Identical Delayed and Fading Channels

Two-Layer Reinforcement Learning for Output Consensus of Multiagent Systems Under Switching Topology.

In this article, the data-based output consensus of discrete-time multiagent systems under switching topology (ST) is studied via reinforcement learning. Due to the existence of ST, the kernel matrix of value function is switching-varying, which cannot be applied to existing algorithms. To overcome the inapplicability of varying kernel matrix, a two-layer reinforcement learning algorithm is proposed in this article. To further implement the proposed algorithm, a data-based distributed control policy is presented, which is applicable to both fixed topology and ST. Besides, the proposed method does not need assumptions on the eigenvalues of leader's dynamic matrix, it avoids the assumptions in the previous method. Subsequently, the convergence of algorithm is analyzed. Finally, three simulation examples are provided to verify the proposed algorithm.

Output Feedback Consensus for High-order Stochastic Multi-agent Systems With Unknown Time-varying Delays

Output Feedback Consensus for High-order Stochastic Multi-agent Systems With Unknown Time-varying Delays

Distributed Adaptive Output Feedback Consensus for Nonlinear Stochastic Multiagent Systems by Reference Generator Approach.

This article investigates the distributed leader-following consensus for a class of nonlinear stochastic multiagent systems (MASs) under directed communication topology. In order to estimate unmeasured system states, a dynamic gain filter is designed for each control input with reduced filtering variables. Then, a novel reference generator is proposed, which plays a key role in relaxing the restriction on communication topology. Based on the reference generators and filters, a distributed output feedback consensus protocol is proposed by a recursive control design approach, which incorporates adaptive radial basis function (RBF) neural networks to approximate the unknown parameters and functions. Compared with existing works on stochastic MASs, the proposed approach can significantly reduce the number of dynamic variables in filters. Furthermore, the agents considered in this article are quite general with multiple uncertain/unmatched inputs and stochastic disturbance. Finally, a simulation example is given to demonstrate the effectiveness of our results.

Distributed Leaderless and Leader-following Consensus for Second-order Heterogeneous Multi-agent Systems Under Input Saturation

Distributed Leaderless and Leader-following Consensus for Second-order Heterogeneous Multi-agent Systems Under Input Saturation

Global Consensus of Double-Integrator Multiagent Systems With Input Saturation by Fully Distributed Event-Triggered and Self-Triggered Controls

Global Consensus of Double-Integrator Multiagent Systems With Input Saturation by Fully Distributed Event-Triggered and Self-Triggered Controls

Dynamic event-triggered quantized secure output consensus of heterogeneous multi-agent systems under DoS attacks.

This paper investigates secure output consensus problem of heterogeneous multi-agent systems (HMASs) under denial-of-service (DoS) attacks. First, an adaptive dynamic compensator depending on local measurement information is designed for tracking the signal of the virtual exosystem. Second, for mitigating network communication load, a novel adaptive control protocol is developed by introducing dynamic event-triggered control and quantized control strategies. Moreover, Zeno behavior can be eliminated under the proposed scheme. Third, the secure output consensus of HMASs under DoS attacks can be guaranteed by satisfying the designed sufficient conditions. Finally, simulation is shown to verify reliability of the proposed control protocol and theory.

Differentially Private Average Consensus of Multi-Agent Systems via Privacy-Based Dynamic Self-Triggered Mechanism

Differentially Private Average Consensus of Multi-Agent Systems via Privacy-Based Dynamic Self-Triggered Mechanism

Bipartite consensus for multi-agent systems over signed networks: A novel dynamic event-triggered mechanism

This paper is concerned with the problem of dynamic event-triggered bipartite consensus control for nonlinear multi-agent systems based on signed networks. A new dynamic event-triggered control mechanism is proposed, whereby an adjustment variable is introduced to dynamically schedule the triggering frequency, enabling the minimization of the triggering times while ensuring system performance. Based on the designed event-triggered control algorithm, sufficient conditions are derived to guarantee that bipartite consensus can be reached by the considered nonlinear multi-agent system. Furthermore, it is proved that Zeno behavior will not occur. Numerical examples are provided in this paper to verify the effectiveness of the proposed control algorithm. The simulation results reveal that, compared with the static event-triggered mechanism and the traditional dynamic event-triggered mechanism, the proposed event-triggered algorithm can further reduce the triggering times and enhance the flexibility of the event-triggered mechanism.

Practical Exponential Stability of Positive Switched Linear System and Its Application in Practical Consensus of Multi-agent System

Practical Exponential Stability of Positive Switched Linear System and Its Application in Practical Consensus of Multi-agent System

Consensus for Heterogeneous Multiagent Systems: Output Rate-Coded Secure Control.

This article investigates an output rate-coded secure control based on backstepping for the consensus of heterogeneous multiagent systems (MASs) with output-triggering condition. Due to the nondifferentiable virtual control inputs caused by discontinuous triggering signals, it presents a technical obstacle in implementing the recursive backstepping, rendering previous results inapplicable. To address this problem, an auxiliary high-order filter is elaborately constructed to guarantee the required-order derivatives of virtual control inputs. As this filter is driven by local triggering consensus error, it allows our MASs to have different system orders and relative degrees. Besides, to reduce communication bit and strengthen communication security, we propose a novel distributed rate-coded algorithm from an encoding-decoding viewpoint. When it is triggered, agent's output is encrypted into an L -length codeword, then transmitted to neighbors without exposing any sensitive system states or real control inputs. It is shown that all the closed-loop system signals are ultimately bounded, and the mean square consensus tracking error can be reduced by appropriately selecting control parameters. Simulations illustrate our theoretical finding.

Distributed consensus of nonlinear stochastic multi-agent systems with input and output delays via predictive control

Distributed consensus of nonlinear stochastic multi-agent systems with input and output delays via predictive control

Leader-follower consensus for nonlinear multi-agent systems under directed topology

This paper investigates the consensus problem for multi-agent systems (MASs) under directed topology. The primary objective is to design the distributed control protocol such that all agents can converge to the state of leader. The distributed control protocol is designed, and we derive sufficient conditions by using Lyapunov stability theory to achieve consensus. Theoretical analysis and numerical simulations are provided to verify the effectiveness of the proposed control protocol.