Conditions For Consensus Research Articles

Reachable set estimation and H∞$H_\infty$ performance for delayed fuzzy multi‐agent systems under false data injection attacks

AbstractAddressed in this paper is the reachable set estimation (RSE) problem for fuzzy‐model‐based leader‐follower multi‐agent systems with time‐varying delays and false data injection attacks. First, the aperiodic sampled‐data control is designed for the follower agents with randomly occurring false data injection attacks. Then, using the Kronecker product, the error system between the leader and the follower is obtained in a compact general form. Next, a novel Lyapunov‐Krasovskii functional is constructed with the knowledge of sampling patterns and time‐varying delays. In the framework of linear matrix inequalities, sufficient consensus conditions are determined from the performance index and Lyapunov theory to guarantee that its reachable set is enclosed by an ellipsoid in the existence of bounded perturbations. In the end, the Duffing Van der Pol oscillator and the single‐link robot arm models are employed to validate the derived theoretical results.

On leaderless consensus of incommensurate order multi-agent systems

This article concerns the leaderless consensus problem of incommensurate-order multi-agent systems. First, a detailed analysis of the consensus between two agents with incommensurate order is shown. From this, one can conclude that consensus behavior exists in such cases. Furthermore, the initial value of the agent with a lower order will decide the consensus state. Second, a general incommensurate order multi-agent system is investigated under the directed ring topology, and the results imply that the consensus behavior also exists in such a topology. At the same time, the initial values of the agent with minimum order will determine the consensus state. Finally, some numerical examples are given to show the effectiveness of the aforementioned theoretical results. In addition, several attempts are given just by simulations when the topology is undirected and connected, and some discussions are conducted in the end.

Consensus of MASs With Input and Communication Delays by Predictor-Based Protocol.

In this article, the consensus problem of multiagent systems (MASs) affected by input and communication delays is investigated. A predictor-based state feedback protocol is used to reach the consensus of linear MASs by delay compensation. In order to analyze the maximum delay under the predictor-based protocol, the overall MASs are equivalent to the feedback interconnection system, including a linear time-invariant system and a time-delay operator, in view of the characteristic of the Laplacian matrix. Then, the maximum delay corresponding to the predictor-based protocol is evaluated by using the small gain theorem (SGT). Finally, two numerical examples are given to verify the effectiveness of the obtained consensus condition.

A hybrid time/event-triggered interaction framework for multi-agent consensus with relative measurements

This paper is concerned with the output-feedback consensus problem of linear multi-agent systems on undirected graphs. Our focus is on reducing sensing and communication burdens between agents. Based on relative output measurements, a dynamic output-feedback (DOF) protocol is proposed, which, by leveraging the structure of the closed-loop dynamics, integrates a hybrid time/event-triggered sampling mechanism such that only intermittent interaction between agents is needed. Consensus conditions are established by the Lyapunov method and numerical simulations are provided for illustrating the effectiveness of the protocol. Compared with the existing results, the proposed DOF protocol has the following merits: (1) they rely on relative output measurements but do not need absolute measurements about agents; (2) they only require agents to intermittently interact with neighbors and thus can greatly reduce sensing and communication burdens between agents; and (3) the designed event-triggering conditions do not need to perform extra reconstruction operations that are computationally demanding.

Distributed optimal consensus of multi-agent systems: A randomized parallel approach

In this paper, a randomized parallel algorithm is proposed to solve the distributed optimal consensus problem of multi-agent systems. Involving both the transient response and the final consensus state, the problem is described as a constrained non-separable optimization problem. Inspired by the randomized Jacobi proximal alternating direction method of multipliers, the proposed algorithm makes it possible for only a fraction of agents to solve their private subproblems in parallel at each iteration, which greatly saves computational resources and enhances running efficiency. The convergence analysis of the algorithm gives fully distributed convergence conditions. A trade-off between the convergence speed and resource savings is then obtained, where the convergence rate is estimated to be at least O1t. Furthermore, the algorithm can be accelerated to enjoy a convergence rate of O1t2 by adaptively adjusting the auxiliary parameters properly. Numerical simulations demonstrate the effectiveness of the theoretical results.

A fast coordination approach for large-scale drone swarm

With the advances in artificial intelligence, robotics, and data fusion, large numbers of drones operating in a coordinated manner will become commonplace for a wide range of commercial and military uses. At present, the application methods of drone swarms are mainly divided into fully autonomous methods and controlled methods with human participation. Because of the limited level of artificial intelligence, controlled drone swarms will be the main way for the application of large-scale drone swarms for a long time. However, there is less research on achieving global coordination in a limited time for a controlled large-scale drone swarm. Therefore, a new large-scale drone swarm framework is proposed firstly in this paper, which achieves global coordination through local interaction and reduces the impact of limited channel resources. Secondly, this paper proposes a local interaction-based fast coordination method and introduces a prediction mechanism, to ensure that large-scale drone swarms can quickly achieve coordination even in the presence of node loss. Moreover, the numerical integration method is used to update the consensus state, so that the drones can increase the iteration period, reduce the number of packets, and further reduce the channel burden. Finally, considering that large-scale drones swarm are usually composed of drone swarms launched at different locations and times, a consensus algorithm considering the merging behavior of drone swarms is also proposed. The simulation results show that the large-scale drone swarm using the proposed architecture can achieve the leader–follower consensus in a very short time and even in a confrontational environment with poor communication conditions. Besides, after the merger of multiple drone swarms, the consensus problem can still be solved in very few iteration cycles.

Dynamic Coordinated Control for Multiconverter Systems via a Multistep Prediction Scheme

Modular DC-DC converters are popular in DC power systems such as demagnetization systems due to their advantages of high efficiency, high reliability, and low current stress on components. However, the dynamic consensus of output currents of the multiple converter degaussing systems (MCDSs) has not been well solved yet, especially when communication delay is considered. In this paper, a novel coordinated control method based on multi-step state predictions with active compensation of delay is proposed to address the poor dynamic consensus performance of currents in MCDSs. The implementation of the scheme consists of two main phases: the design of a multi-step state predictor for MCDSs and the optimization of the coordinating cost of currents. The multi-step state predictor can estimate immeasurable future states of converters over a large horizon length, which presents a novel approach to the current regulator design. The optimal control protocol is derived by minimizing a distributed coordinating performance index function (PIF) for the output currents. This optimization of the PIF minimizes the consensus error between output currents for converters and compensates for communication constraints. Further, the conditions for simultaneous stability and consensus of the closed-loop degaussing system with the distributed multi-step state prediction controller are given. Finally, the performance of the proposed scheme is verified by numerous case studies in an FPGA-based OPAL-RT experimental testbed.

Eurasian Economic Union: Mechanisms and meanings of social-humanitarian cooperation

The relevance of the research is determined by the need in new opportunities to improve the effectiveness of integration processes in the Eurasian Economic Union (EAEU) under the increasing global instability. The author shows the importance of social-humanitarian cooperation for integration processes, describes its mechanisms, tools and meanings. The article is based on the materials of the governing bodies of the EAEU, state and non-state organizations of the member countries, current publications of the mass media and studies conducted by the Institute of Demographic Research in 2019- 2023. The author describes both the current state of cooperation between the member countries and its problems, such as the local nature of joint events held on a bilateral basis and having a small integration effect; the declining use of the Russian language in the post-Soviet space; the increasing denial of the Soviet past and a low level of support for integration among the younger groups; the lack of an acceptable consensus of the member states in assessing the depth of integration processes; overestimated expectations from the development of countries within the Union; the lack of institutional basis for social-humanitarian interaction and of supranational structures that ensure work with the population of the EAEU. The author sees the prospects for the development of humanitarian cooperation within the Eurasian integration in productive communication projects of a mass nature, which aim at a large audience and form the potential for integration of countries and peoples. The author argues that social-humanitarian projects of Eurasian integration will inevitably require content interesting for younger generations and active social groups, so that cooperation meanings would contribute to the formation of a common socialhumanitarian space of the EAEU.

Group consensus for competitive multiagent systems with input saturation and intermittent communication using current and outdated states

This paper investigates group consensus control for first-order multi-agent systems (MASs) with input saturation and intermittent communication. A novel class of distributed group consensus protocols is designed by combining current and outdated states of agents, which differs from the standard one using only current states. Sufficient conditions for group consensus are derived for MASs without two conservative assumptions required by previous literature. The proposed protocol can accelerate the convergence speed of MASs by choosing appropriate outdated states. Several examples are provided to illustrate the effectiveness of our results.

Sliding mode based prescribed-time consensus tracking control of second-order multi-agent systems

In this work, we investigate the prescribed-time consensus tracking problem for second-order multi-agent systems under directed topology. A new hybrid distributed observer for each follower is developed to estimate the states of the leader in prescribed time. Based on the observer, a novel prescribed-time sliding mode surface that is nonsingular and the corresponding tracking controller are designed such that the full state consensus tracking is achieved within a prescribed time. The salient feature of the proposed control scheme lies in that not only accurate tracking can be achieved within the prescribed time but also the numerical implementation problem arising from the infinite time-varying gain is avoided. The effectiveness of the proposed method is confirmed by the numerical simulation.

Dissonance minimization and conversation in social networks

We are examining social learning in networks, where agents aim to minimize cognitive dissonance resulting from disagreement by adjusting their statements in conversations to align with those of their associates, rather than truthfully sharing their beliefs. Our analysis investigates the impact of this adjustment, known as audience tuning, on belief revision, limiting beliefs, consensus conditions, and convergence speed. Our findings demonstrate that audience tuning facilitates extensive belief propagation beyond immediate associates, resulting in faster convergence in most of the societies considered. It also leads to a redistribution of influences on long-run beliefs, favoring agents with lower dissonance sensitivity. We also show that endogenous changes in the network, driven by dissonance minimization, can impede society from reaching a consensus.

An overview of consensus models for group decision-making and group recommender systems

Group decision-making processes can be supported by group recommender systems that help groups of users obtain satisfying decision outcomes. These systems integrate a consensus-achieving process, allowing group members to discuss with each other on the potential items, adapt their opinions accordingly, and achieve an agreement on a selected item. Such a process, therefore, helps to generate group recommendations with a high satisfaction level of group members. Our article provides a rigorous review of the existing consensus approaches to group decision-making. These approaches are classified depending on the applied consensus models such as reference domain where a set of group members or items is selected for calculating consensus measures, coincidence method that calculates the consensus degree between group members depending on the coincidence concept, operators that aggregate user preferences, guidance measures where the consensus-achieving process is guided by different consensus measures, and recommendation generation and individual centrality that enhance the role of a moderator or a leader in the consensus-achieving process. Further consensus techniques for group decision-making in heterogeneous and large-scale groups are also discussed in this article. Besides, to provide an overall landscape of consensus approaches, we also discuss new consensus models in group recommender systems. These models attempt to improve basic aggregation strategies, further consider social relationship interactions, and provide group members with intuitive descriptions regarding the current consensus state of the group. Finally, we point out challenges and discuss open topics for future work.

Event-triggered boundary consensus control for multi-agent systems of fractional reaction–diffusion PDEs

The distributed consensus is considered for multi-agent systems (MASs), which characterized by fractional reaction–diffusion partial differential equations (RDPDEs) in this paper. Based on Lyapunov technique and linear matrix inequalities (LMIs) theory, the consensus can be realized via two novel event-triggered boundary control schemes. Firstly, a novel convergence principle subject to finite time is presented for the continuously differentiable function. Secondly, the cooling fin on surface of high-speed aerospace vehicle is remodeled by fractional RDPDEs system, and the well-posedness of presented system is discussed applying the monotone iterative approach. Thirdly, according to the presented static event-triggered boundary control strategy, the consensus criterion in finite time is addressed in the form of LMIs, in addition, the settling time is calculated accurately. Applying the dynamic event-triggered control protocol, the Mittag-Leffler (M-L) consensus condition is achieved. Moreover, the Zeno behaviors are ruled out for proposed event-triggered mechanisms. Finally, the high-speed aerospace vehicle model is presented to verify the effectiveness of the control performance.

Model-Based Distributed Asynchronous Sampling for Multiagent Consensus With Event-Detecting Delays and Network Delays

In this paper, the practical average consensus problem of linear multi-agent systems with model-based distributed asynchronous sampling is investigated. Both internal event-detecting delays and external network delays are allowed in systems. Data-sampling instants are generated asynchronously by local event-triggering conditions. Particularly, data-sampling instants and event-triggering instants of each agent are also asynchronous due to the existence of event-detecting delays. Prediction models are utilized in detecting events and updating control inputs. Artificial interpolation instants are introduced in each sampling interval to address theoretical challenges brought by internal and external delays. To deal with this kind of complex asynchronous setup with multiple time delays, based on Barbalat's Lemma, a new procedure for deriving conditions for average consensus and a theoretical analysis approach are presented.

Delay Robustness of Consensus Algorithms: Continuous-Time Theory

Consensus among autonomous agents is a key problem in multi-agent control. In this paper, we consider averaging consensus policies over time-varying graphs in presence of unknown but bounded communication delays. It is known that consensus is established (no matter how large the delays are) if the graph is periodically, or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">uniformly</i> quasi-strongly connected (UQSC). The UQSC condition is often believed to be the weakest sufficient condition under which consensus can be proved. We show that the UQSC condition can actually be substantially relaxed and replaced by a condition that we call <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aperiodic</i> quasi-strong connectivity (AQSC), which, in some sense, proves to be very close to the necessary condition (the so-called integral connectivity). Under the assumption of reciprocity of interactions (e.g., for undirected or type-symmetric graphs), a necessary and sufficient condition for consensus in presence of bounded communication delays is established; the relevant results have been previously proved only in the undelayed case.

Fast Consensus of High-Order Multiagent Systems

In this paper, the fast consensus problem of high-order multi-agent systems (MASs) under undirected topologies is considered. The direct link between the consensus convergence rate and the control gains is established. A gradient descent based algorithm is proposed to optimize the convergence rate. By applying the Routh-Hurwitz stability criterion, the lower bound on the convergence rate is derived, and explicit control gains are derived as conditions to achieve the optimal convergence rate. Moreover, a protocol with time-varying control gains is designed to achieve the finite-time consensus. Explicit formulas for the time-varying control gains and the final consensus state are given. Numerical examples and simulation results are presented to illustrate the obtained theoretical results.

Transmission-Constrained Consensus of Multiagent Networks

This paper studies the consensus problem for multiagent systems with transmission constraints. A novel model of multiagent systems is proposed where the information transmissions between agents are disturbed by irregular distortions or interferences (named transmission constraint functions), and this model is universal which can be applied in many cases, such as interval consensus and discarded consensus. In the transmission-constrained consensus problem, we obtain the necessary and sufficient condition that agents can converge to state consensus. Furthermore, a more general case is studied in which the system reaches an equilibrium. Based on some techniques of stability theory, the existence, uniqueness and stability of the system equilibrium point can be proven, which means the system can reach an asymptotically stable equilibrium. Moreover, the state values of the equilibrium are only decided by the network structure and transmission constraint functions, but not the agents' initial states. Finally, numerical simulations are presented to illustrate the proposed theorems and corollaries.

Distributed secure consensus for multiagent systems based on removing intra-cluster coupling restrictions and its application to energy systems

Cluster consensus of multiagent systems has provided analytical techniques for various industrial domains. As agents work in networked environments, their secure consensus control becomes essential desirable in response to cyber attacks. At that point, we investigate the secure cluster consensus in directed network systems under deception attacks and mixed delays. First, a control strategy for improving arbitrarily fixed topologies based on an extended state observer is proposed to ensure cluster consensus. In the framework of the proposed strategy, several criteria are derived to guarantee cluster consensus for agents. Second, different from the current works that require sufficiently strong intra-cluster coupling strength, the proposed consensus condition ensures fewer intra-cluster coupling restrictions. Third, the Halanay inequality is used to handle the mixed delays and reduce the parameters in the consensus criterion, which improves the efficiency of verifying the consensus. Finally, the simulation results on the IEEE 39-bus energy system are provided for validating the effectiveness of the proposed method, while achieving excellent tracking performance for the frequency and power deviations.

Leader-following identical consensus for Markov jump nonlinear multi-agent systems subjected to attacks with impulse

The issue of leader-following identical consensus for nonlinear Markov jump multiagent systems (NMJMASs) under deception attacks (DAs) or denial-of-service (DoS) attacks is investigated in this paper. The Bernoulli random variable is introduced to describe whether the controller is injected with false data, that is, whether the systems are subjected to DAs. A connectivity recovery mechanism is constructed to maintain the connection among multi-agents when the systems are subjected to DoS attack. The impulsive control strategy is adopted to ensure that the systems can normally work under DAs or DoS attacks. Based on graph theory, Lyapunov stability theory, and impulsive theory, using the Lyapunov direct method and stochastic analysis method, the sufficient conditions of identical consensus for Markov jump multi-agent systems (MJMASs) under DAs or DoS are obtained, respectively. Finally, the correctness of the results and the effectiveness of the method are verified by two numerical examples.

Exponential Consensus of Multiagent Systems Based on Nonlinear Parabolic PDEs via Intermittent Boundary Control

The exponential consensus issue is investigated for leader-following multiagent systems (MASs) based on nonlinear parabolic partial differential equations (PDEs) on a directed graph via intermittent boundary control (IBC) methods. On the one hand, when the system’s state is accessible, an IBC protocol is designed based on the transfer information generated by the agent’s communication with its neighbors and the information coupling at the boundary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x= l$</tex-math> </inline-formula> , and the sufficient conditions for exponential consensus of leader-following MASs are obtained. On the other hand, when the system’s state is not available completely, the agent’s state is estimated by the proposed observer, and the observer’s coupling information and the boundary coupling information of the agent are adopted to design an IBC protocol to solve the leader-following consensus issue. Finally, two numerical simulations are supplied to account for the obtained theoretical results.