Consensus Problem Of Multi-agent Systems Research Articles

Adaptive Event-Triggered Consensus of Linear Multiagent Systems With Resilience to Communication Link Faults for Digraphs

This brief investigates the leader-follower consensus problem for multiagent systems (MASs) with resilience to unknown communication link faults. To deal with the unknown faults and avoid using global information, the adaptive event-triggered observers are designed to estimate the leader state, namely, resilience for communication link faults is transformed into the design observers by adaptive control technology. Then, based on the designed observers, controllers are designed to stabilize the given MASs. Finally, an example is introduced to demonstrate the effectiveness of the obtained results.

Event-Based Tracking Consensus for Multiagent Systems With Volatile Control Gain.

This work investigates the tracking consensus problem of multiagent systems over directed networks, where the control gains follow certain volatile patterns. Some event-based consensus protocols are formulated so as to reduce the redundant execution of control. By using an extended differential inequality with a time-dependent coefficient, criteria for tracking consensus under time- and state-dependent triggering conditions are constructed, respectively. It is proved that the time average of the control gain, together with the agent dynamics, network topology, and triggering conditions, governs the consensus despite the fluctuation of control gain. The derived theorem can be utilized to ensure consensus with intermittent strategies aiming to lessen the burden in communications, including aperiodic on-off control with periodic perturbation and pulse-modulated on-off control. Unlike existing works, the requirement of a positive lower bound of control ratios is removed and, thus, a wide range of control gain patterns is possible, signifying higher flexibility in intermittent policy design. Finally, numerical examples are provided to further illustrate the theoretical results.

Consensus control of multi-agent systems with deception attacks using event-triggered adaptive cognitive control

This paper presents a novel event-triggered adaptive cognitive control to address the consensus problem of multi-agent systems (MASs) with a Leader under deception attacks. By using the reinforcement learning, adaptive radial basis function (RBF) neural networks and sliding mode control, an adaptive cognitive control is developed. This control has two parts: Actor and Critic. The Actor is designed by using adaptive RBF neural networks and sliding mode control, named adaptive sliding mode control. It is used to control the agent. The Critic is constructed utilizing the adaptive RBF neural networks, to evaluate the control performance of the Actor. In addition, to reduce the communication cost, an event triggered mechanism is designed. The Lyapunov stability analysis shows that the proposed event-triggered adaptive cognitive control can ensure the stabilization of the MASs in case of deception attacks. Simulations are performed to validate the feasibility of the proposed event-triggered adaptive cognitive control, indicating that it can decrease the effects of deception attacks and ensure that all Followers can synchronize to the Leader.

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.

Reinforcement learning based proportional–integral–derivative controllers design for consensus of multi-agent systems

This paper develops a novel Proportional–Integral–Derivative (PID) tuning method for multi-agent systems with a reinforced self-learning capability for achieving the optimal consensus of all agents. Unlike the traditional model-based and data-driven PID tuning methods, the developed PID self-learning method updates the controller parameters by actively interacting with unknown environment, with the outcomes of guaranteed consensus and performance optimization of agents. Firstly, the PID control-based consensus problem of multi-agent systems is formulated. Then, finding the PID gains is converted into solving a nonzero-sum game problem, thus an off-policy Q-learning algorithm with the critic-only structure is proposed to update the PID gains using only data, without the knowledge of dynamics of agents. Finally, simulations are given to verify the effectiveness 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.

Input-observer event-based consensus in linear multi-agent systems

This paper provides an input-observer event-based controller to solve consensus problems in multi-agent systems with general linear dynamics over fixed directed and undirected network topologies. A Lyapunov-based event condition is proposed to achieve consensus using neighbors’ output information. The proposed method is distributed in the sense that the event detectors only use neighbors’ information, and the controller updates its value by using intermittent communication. Finally, an example is provided to illustrate the effectiveness of theoretical results.

Finite-Time Leader-Following Consensus of Multiagent Systems With Actuator Faults and Input Saturation

This article studies the fault-tolerant leader-following consensus problem for multiagent systems with input saturation. The main contribution is to present a modified low-and-high gain feedback approach to deal with multiple actuator faults, including partial loss of effectiveness, outage, and stuck simultaneously. First, without consideration of saturation, a distributed fault-tolerant control scheme is put forward by the adaptive technique, and a practical finite-time stability result is established. Second, by employing the fault-tolerant theory and introducing a novel form of parametric algebraic Riccati equation, a modified low-and-high gain feedback approach is developed for the saturated control strategy. It is proven that the practical finite-time stability can be achieved, and both the steady-state consensus error and the settling time can be well estimated. Finally, numerical simulations are provided to validate the effectiveness of the theoretical results.

Privacy-Preserving Average Consensus via Finite Time-Varying Transformation

The privacy-preserving average consensus problem in multi-agent systems means that all agents in the system can reach an agreement on the average of their initial values, but guarantees that their initial states are private. In this paper, a new approach is proposed to solve this problem, furthermore, it can solve both asymptotic time consensus problem and prescribed-time consensus problem. The core idea of this approach is to construct functions which can mask the real states of agents in finite time. That is, within a certain period of time, what agents transmit is no longer their real state values, but the values acting on the designed functions. These designed functions are time-varying, local (i.e., determined independently by each agent), and converging to the true states in finite time. It is proved that the correctness (accurate calculation of global average value) and privacy (the initial values of agents are not speculated by other agents) can be guaranteed under our method. Finally, some numerical simulations are given to verify the effectiveness of our approach.

Secure Consensus of Multiagent Systems With Input Saturation and Distributed Multiple DoS Attacks

The secure consensus problem of multiagent systems with input saturation and denial-of-service (DoS) attacks constraints is an interesting research problem. To solve this problem, the assumptions that all the agents own the same saturation level and suffer the same DoS attacks from a single adversary are usually made. This brief removes the above assumptions and investigates the secure consensus problem of multiagent systems with different saturation levels and multiple DoS attacks. The studied multiagent systems have different layers, in which different saturation levels are studied for different layers. Moreover, the DoS attacks are launched from different adversaries and will cause different effects for different agents. To achieve the desired objective, two different consensus protocols for agents in different levels are first designed using the low-gain technique. Then, the investigated dynamic system under DoS attacks is modeled by a switched system by categorizing the DoS attacks into several types. The controller is proposed by solving parametric algebraic Riccati equation (ARE). Sufficient conditions for the DoS attack duration on each channel are derived.

Sampled-based consensus of multi-agent systems with bounded distributed time-delays and dynamic quantisation effects

In this paper, we are concerned with the sampled-based consensus problem of multi-agent systems with bounded distributed time-delays and quantisation effects. A dynamic quantisation scheme is introduced to save the constrained communication resources, where some adjustable parameters are introduced to exclude the phenomena of quantiser saturation. In addition, to reduce the actuation burden of controller and quantiser cost, a sampled-data control strategy is employed to investigate the consensus problem. Several sufficient criteria are derived to achieve consensus of multi-agent systems based on the matrix theory and Lyapunov control techniques. Finally, two numerical examples are provided to demonstrate the effectiveness of the derived results.

Event-triggered leader-following consensus of multi-agent systems under semi-Markov switching topology with partially unknown rates

An event-triggered leader-following consensus problem for multi-agent systems with nonlinear dynamics was investigated in this study. The interaction topologies among the agents that we considered are randomly switched ones, governed by a semi-Markov process with partially unknown rates. By building the state error model between the leader and followers, the consensus problem is first converted into a stability problem. Moreover, an event-triggered transmission scheme based on sampling data was proposed to reduce communication redundancy. The consensus controller and event-triggered parameters can be designed effectively. By constructing a Lyapunov–Krasovskii functional (LKF) with a triple integral, the sufficient conditions required to guarantee the event-triggered consensus can be reached with respect to the linear matrix inequalities (LMIs). Ultimately, the validity of the theoretical results is demonstrated by a numerical example.

Leader-Follower finite-time consensus of multiagent systems with nonlinear dynamics by intermittent protocol

This paper deals with the leader-follower finite-time consensus problem for multiagent systems with nonlinear dynamics via intermittent protocol. The topological structure of the followers is undirected or balanced digraph. Different from most existing works concerning nonlinear dynamics (satisfies Lipschitz continuity), the nonlinear dynamics of each agent satisfies Hölder continuity in this paper. In light of the finite-time control technique, the intermittent control protocol is designed to reach accurate leader-follower finite-time consensus. It is justified that the leader-follower finite-time consensus can be realized if the length of communication is greater than a critical value by using limit theory. Finally, two numerical examples are exhibited to validate the effectiveness of the proposed scheme.

Terminal Iterative Learning Scheme for Consensus Problem in Multi-Agent Systems with State Constraints

In this paper, we investigate the consensus problem of multi-agent systems with state constraints. To achieve the consensus effectively, the terminal iterative learning approach is proposed. This learning strategy is designed without the tracking error. And the consensus state is obtained by the the information interaction between agents. Meanwhile, the constraint condition holds in terms of our learning strategy. It shows the consensus conditions ensure the achievement of the constraints. Finally, a numerical simulation is given to illustrate the effectiveness of the main results.

A unified approach for the influences of negative weights on system consensus

In this paper, the influences of negative weights on the consensus problems of multi-agent systems are investigated. While the system is subject to external attacks or agents in the system break down, there are errors in information transmission between agents. As a result, for non-negative systems, the connection weights between agents may change, or even change from positive to negative. In this paper, we provide a unified approach to deal with the problem of how to ensure the consensus of the system when the connection weight becomes negative. It is found that the consensus of multi-agent systems and general linear multi-agent systems will be guaranteed while the weights change to a certain extent without changing the protocol and feedback gains. We obtain a necessary and sufficient condition to ensure that the system can still reach asymptotic consensus when the connection weight is negative. The result is applicable to first-order, high-order integrator type of multi-agent systems as well as the general linear multi-agent system.

Event‐triggered leader‐following consensus for a class of nonlinear multiagent systems with time‐varying delay

AbstractThis article studies the consensus problem for discrete‐time nonlinear multiagent systems with time delay. Based on an asynchronous event‐triggered mechanism where local information of a communication graph is involved, a distributed consensus protocol is proposed to reduce the network communication congestion for achieving state consensus for multiagent systems with nonlinear perturbations. To avoid complications involving data fusion, this distributed consensus protocol allows every agent to broadcast its state at its own triggering condition instead of using continuous updates and without continuous monitoring of the triggering condition. To save the energy consumption involved in a consensus protocol, the proposed event‐triggering guaranteed cost is investigated in this article for multiagent systems. We select an agent as a leader that is constrained by its neighbors and controlled by the proposed protocol as other agents. It has been theoretically demonstrated that the consensus problem of multiagent systems with nonlinear perturbation and time delays can be achieved if the control gains and the triggering parameters are appropriately selected. Sufficient conditions are given to guarantee that the agents achieve consensus. Moreover, the gain matrix and triggering parameters of the proposed protocol are cast into matrix inequalities conditions. A simulation example is given to illustrate the effectiveness of the theoretical results.

Adaptive event-triggered consensus of multi-agent systems with general linear dynamics

This paper is concerned with adaptive event-triggered consensus of general linear multi-agent systems (MASs). Leaderless consensus and leader-following consensus are both considered. In order to avoid dependence on global information about system topology and reduce communication frequency, distributed adaptive event-triggered consensus protocols are designed. Through model transformation, the consensus problems of MASs are transformed into the stability problems of the corresponding error systems. By using algebraic graph theory and Lyapunov stability theory, some sufficient criteria for MASs to achieve consensus are obtained. Meanwhile, it is proved that the proposed event-trigger conditions can exclude Zeno behaviour effectively. One simulation example is provided to validate the effectiveness of obtained theoretical results.

Finite- and Fixed-Time Consensus Protocols for Multi-Agent Systems With Time-Varying Topologies

This letter presents finite- and fixed-time protocols, which solve the consensus problem in multi-agent systems with time-varying directed topologies. We show that the proposed distributed protocols solve the consensus problem under switching topologies, which are jointly strongly connected. These distributed protocols homogenize the multi-agent networks, which make the overall system robust against disturbances. We employ the homogeneity property of the vector fields, graph theory, Lyapunov stability theory and convex analysis to show the finite- and fixed-time stability of the multi-agent systems. Numerical examples are presented to demonstrate the effectiveness of the proposed control methods.

Finite-Time Average Consensus Control of Multi-Agent Systems Based on the Aperiodically Intermittent Control

This study investigates the finite-time consensus problem of multi-agent systems under an aperiodically intermittent control. By designing an appropriate control protocol, the whole control process can be divided into two states, namely, the continuous communication time period and the interrupted communication time period. These two control states are aperiodic. Then, according to the designed control protocol, the appropriate Lyapunov function is constructed using the segmented state information. Subsequently, the corresponding state model of the multi-agent system is introduced, and the relevant conditions for the consensus of the multi-agent system under an aperiodically intermittent control are obtained using norm inequality and the corresponding properties of the Kronecker product. After determining the consensus of the general model, the nonlinear term and uncertainty term are added, and the consensus is realized using the control protocol. The control method presented in this research can avoid continuous communication, and the aperiodic control process is more in line with the relevant needs of the actual project than the periodic control process. As a result, the proposed method can effectively reduce energy consumption and fit actual projects. Finally, the effectiveness of the theory is proven via numerical simulation.

Sampling Consensus of 2nd-Order Multi-Agent Systems Based on Time-Varying Topology

The sampling consensus of second-order multi-agent systems with time-varying topology is investigated based on the constant position difference and consistent speed. Firstly, the virtual leader is introduced and the sampling consensus problem of multi-agent systems is transformed into the stability problem of the corresponding error system. Secondly, by estimating the sampling error, the influence of sampling error on system consistency is studied. Finally, by virtue of the Lyapunov stability theory, the stability of the constructed error system is analyzed, and a sufficient condition for the stability of the error system is given. The numerical simulation results verify the effectiveness and correctness of the theoretical analysis.