Consensus Problem Research Articles

Privacy-preserving finite-time average consensus and its application to power allocation of battery energy storage systems

In this paper, the privacy-preserving problem of finite-time discrete-time average consensus is studied by adding random numbers. The privacy leakage conditions are given for systems with curious but not malicious nodes and eavesdroppers, respectively. By introducing the random numbers and node decomposition mechanism, the privacy information of the nodes cannot be estimated by the adversaries. The proposed algorithm is applied to the power allocation problem of distributed battery energy storage systems. Based on the previous proposed multi-rate sampling method, the privacy-preserving finite-time discrete-time average consensus is utilized to estimate the accurate average value within finite steps. The accurate power allocation based on the same relative SoC variation rate can be achieved with the privacy preservation of the transmission information. Finally, based on a networked battery energy storage system, simulation studies are presented to verify the effectiveness of the proposed method.

Fixed‐time consensus of networked Euler–Lagrange systems over event‐based communication under DoS attacks

AbstractThis article focuses on fixed‐time consensus of networked Euler–Lagrange systems (NELSs) over event‐based communication under denial‐of‐service (DoS) attacks. First of all, a basic fixed‐time consensus algorithm is developed for NELSs, where a general fixed‐time communication triggering scheme through error decomposition method is designed for decreasing communication frequencies while avoiding singularity. Then, to fulfil the consensus problem of NELSs in the presence of DoS attacks, a novel fixed‐time resilient algorithm is further presented by the basic algorithm, where the effective attack interval is redefined for carrying out the algorithm design. Furthermore, a hierarchical fixed‐time control framework with privacy preservation is introduced for the consensus problem of NELSs under DoS attacks. Meanwhile, a self‐triggered scheme is employed for the above algorithms to lower the update frequencies of control inputs. The stated algorithms possess a uniformly constrained upper bound on the convergence time, and are resilient as well as responsive to DOS attacks while saving control resources significantly. Finally, numerous illustrative examples are given for demonstrating the efficacy of the derived schemes.

Distributed quantized secure bipartite consensus of linear multi‐agent systems with switching topologies and sequential scaling attacks

AbstractThis paper considers the secure distributed control consensus problem of linear multi‐agent systems (MASs) under switching topologies, subject to intermittent sequential scaling attacks, which was compelled to scaling factor, attack frequency, duration and cooperative‐competitive networks. First, the scenario of a fixed topology is considered, and a novel control protocol combined with a logarithmic quantizer and relative state measurements of neighbouring agents is discussed. The sighed graph is utilized to characterize the communication topology determined by the information flow directions and captured by the graph Laplacian matrix. After that, sufficient conditions for effectiveness of the developed control methods in guiding the MASs to secure bipartite leader‐following consensus are constructed. Second, the scenario of switching topologies is considered, and it is derived that the secure bipartite consensus will be achieved if the designed state feedback control protocol with the scaling factor, the attack duration, attack frequency and switching signal are selected properly. At last, to prove the effectiveness of the designed controllers, a simulation example depended on the real‐word actual military is introduced.

Consensus of linear multi‐agent systems under switching topology by sampled‐data output feedback control

AbstractThis paper studies both synchronous and asynchronous consensus problems for linear multi‐agent systems under switching topology. A novel distributed continuous‐discrete observer is established by solely using the relative sampled output messages, which needs neither to store messages from neighboring agents nor estimate the information of itself and all neighbors. Based on the estimation provided by the distributed observer, a distributed output feedback control with digital form is synthesized, which allows each agent to update the value of its controller at the synchronous/asynchronous sampling instants. It is of interest to see that, for the class of chain‐integrator multi‐agent systems, the proposed control approach allows the sampling periods to be chosen freely and thus would be more practical in some situations from the perspective of energy saving. The theoretical results are illustrated by formation flying of spacecraft and synchronization of multiple double‐integrators.

Adaptive output consensus of heterogeneous nonlinear multi‐agent system under random link failures with partially unknown transition rates

AbstractConsidering the complexity of communication environment in reality, this paper investigates the adaptive output consensus problem for heterogeneous nonlinear multi‐agent system (MAS) under random link failures, in which connection of each link may suffer from link failure. The major challenge lies in dealing with the coupling among different nonlinearities and integrator orders of heterogeneous agents while the distributed communication may fail randomly. Hence, a two‐level distributed adaptive control scheme based on the virtual model‐reference strategy will be presented. In the first level, virtual reference models are constructed to deal with the uncertainties caused by the random link failures, and a distributed consensus control strategy is designed based on the established communication observer of each agent. In the second level, an adaptive backstepping tracking controller drives each agent's output to follow its virtual reference model and compensate for the agent's uncertainties. The mean square stability of the controlled MAS has been rigorously proved. An illustrative example is presented to demonstrate the effectiveness of the given control scheme.

Event-triggered predictive control for cooperation-competition multi-agent systems under DoS attacks

This paper concerns the bipartite consensus problem of multi-agent systems(MASs) with competitive- cooperative network topology under denial-of-service (DoS) attacks. Firstly, this work extensively analyzes the competitive phenomena that may exist in the information interchange of agents in contrast to the single cooperative behavior between agents. Based on this, some necessary conditions are provided for the system to attain the bipartite consensus. In addition, the event-triggered mechanism (ETM) effectively lowers unnecessary information sharing between agents and eliminates Zeno behavior. Furthermore, the predictive method provides the system with exceptional resistance against common energy-limited DoS attacks and the ability to compensate for information loss caused by DoS attacks. Finally, a numerical simulation proves that the proposed approach is feasible.

Консенсус как база общественного диалога

The article about problem of consensus as social dialogue basis. Necessary consensus condition is value core as world out-look attitudes community. Author analyses risks of both social community split because of extreme world out-look attitudes pluralism and social uniformity reaching to totalitarian form. Author highlights risk of transformation democracy into ideocracy because of subjection all aspects of civil life to political and ideological agenda.

Robust H∞ consensus for uncertain linear multi-agent systems on directed topologies: A dynamic event-triggered strategy

Considering the asymmetry of the system matrix caused by directed communication networks, a dynamic event-triggered control protocol for the robust [Formula: see text] consensus of uncertain linear multi-agent systems accompanied by external disturbances on directed topologies is proposed. Through the introduction of the controlled output and generalized algebraic connectivity for directed graphs, the consensus problem is converted to the event-triggered stabilization of the uncertain linear closed-loop system with disturbance. On the basis of the relative state of neighbor agents at event-times and the introduced dynamic variables, a dynamic event-triggered control protocol is put forward, and the linear matrix inequality sufficient conditions for the system to achieve robust [Formula: see text] consensus are obtained after a rigorous proof. Then, linear matrix inequalities are further decoupled to greatly reduce the computational complexity, and the parameters of the control protocol are determined by solving the decoupled linear matrix inequalities. Finally, simulations are applied for the verification of conclusions.

Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach

Abstract This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.

Resilient data‐driven asymmetric bipartite consensus for nonlinear multi‐agent systems against DoS attacks

AbstractIn this article, we study an unified resilient asymmetric bipartite consensus (URABC) problem for nonlinear multi‐agent systems with both cooperative and antagonistic interactions under denial‐of‐service (DoS) attacks. We first prove that the URABC problem is solved by stabilizing the neighborhood asymmetric bipartite consensus error. Then, we develop a distributed compact form dynamic linearization method to linearize the neighborhood asymmetric bipartite consensus error. By using an attack compensation mechanism to eliminate the adverse effects of DoS attacks and an extended discrete state observer to enhance the robustness against unknown dynamics, we finally propose a distributed resilient data‐driven adaptive control (DDAC) algorithm to solve the URABC problem. A numerical example validates the proposed results.

Guaranteed-performance consensus for multi-agent systems with Lipschitz nonlinearity

This paper mainly addresses the guaranteed-performance consensus problem of multi-agent systems (MASs), under the energy constraints and Lipschitz nonlinear dynamics. First, to reach consensus under energy constraints, the consensus protocol and the quadratic performance function are proposed. Afterward, by using the properties of nonsingular transformation matrix and Lipschitz’s nonlinear representation, the consensus function conditions are expressed. Moreover, considering the guaranteed-performance cost, this paper designs the quadratic performance function derived from the Riccati inequality and Lyapunov–Krasovskii theorem. Eventually, numerical simulations are implemented to validate the theoretical results.

Distributed Control for Nonlinear Time-Delay Multiagent Systems: Hybrid Saturation-Constraint Impulsive Approach.

This article mainly studies the problem of impulse consensus of multiagent systems under communication constraints and time delay. Considering the limited communication bandwidth of the agent, global and partial saturation constraints are considered. In addition, so as to further improve communication efficiency by reducing communication frequency, the novel control protocol combining event-triggered strategy and general impulse control protocol is proposed. Under this kind of novel control protocol, the communication frequency of multiagent systems can be reduced while avoiding "Zeno behavior." Through theoretical analysis, sufficient conditions for the systems to achieve consensus are obtained for the above two saturation constraint cases. In the end, the effectiveness of the novel protocols is proved by providing two different simulation instances.

Stubborn Observer for Leader-Following Consensus of Nonlinear Multiagent Systems With Application to Spacecraft.

In this article, the leader-following consensus problem is investigated for a class of nonlinear multiagent systems with transmission outliers. First, through the relative output information and observer states of neighbor agents, a distributed stubborn reduced-order observer is proposed to estimate the leader-following consensus error which is affected by abnormal and isolated transmission outliers. Moreover, considering that the leader agent in practice is a controllable plant, another distributed stubborn reduced-order observer is designed by using the relative information and inputs of neighbor agents. Sufficient conditions are established in terms of the Laplacian matrix such that two stubborn reduced-order observers are convergent and the studied nonlinear multiagent system could achieve leader-following consensus with directed topology. Finally, an example of the multispacecraft system is provided to illustrate the effectiveness of the proposed methodology.

Distributed Leader-Following Consensus of Feedforward Nonlinear Delayed Multiagent Systems via General Switched Compensation Control.

This work examines the distributed leader-following consensus problem of feedforward nonlinear delayed multiagent systems involving directed switching topologies. In contrast to the existing studies, we focus on time delays acting on the outputs of feedforward nonlinear systems, and we permit that the partial topology dissatisfy the directed spanning tree condition. In the cases, we present a novel output feedback-based general switched cascade compensation control method that addresses the above-mentioned problem. First, we put forward a distributed switched cascade compensator by introducing multiple equations, and we design the delay-dependent distributed output feedback controller with the compensator. Subsequently, when the control parameters-dependent linear matrix inequality is met and the switching signal of the topologies obeys a general switching law, we prove that the established controller can render that the follower's state asymptotically tracks the leader's state by employing an appropriate Lyapunov-Krasovskii functional. The given algorithm allows output delays to be arbitrarily large and increases the switching frequency of the topologies. A numerical simulation is presented to demonstrate the practicability of our proposed strategy.

Differentially Private Consensus for Second-Order Multiagent Systems With Quantized Communication.

This article considers the differentially private consensus problem of discrete-time second-order multiagent systems with partially measurable states and limited communication channel capacity, where only the integer-value information of agents can be transmitted. To reduce the potential risk of state information disclosure in digital communication, a differentially private consensus algorithm via dynamic encoding-decoding is proposed for the second-order multiagent system to make agents achieve mean-square consensus by transmitting quantized integer values with privacy protection. To deal with the uncertainty of the quantizer saturation, the statistical analysis is given for the boundedness of the input of quantizers. It is shown that the expectation of the minimum memory capacity of quantizers is 2 bits. Finally, some simulation results are given to visualize our conclusions.

Distributed Event-Triggered Quantized Fault-Tolerant Control of Linear Multiagent Systems With External Disturbances and Parameter Uncertainties.

In this article, the issue of fault-tolerant leader-following consensus under a distributed dynamic event-triggered mechanism is addressed for linear multiagent systems (MASs) in the presence of unknown parameter uncertainties, external disturbances, and actuator faults, including loss of effectiveness and bias, in which the mechanism is with quantized state measurements. Due to the fact that information is transmitted via a bandwidth-limited communication network, a quantized control scheme with a uniform quantizer is introduced for leader-following consensus. In order to decrease the communication load and save the limited communication network resources, a distributed event-triggered mechanism is studied for leader-following consensus problem of linear MASs with quantized state measurements. In the presence of actuator faults, external disturbances, and unknown parameter uncertainties, an adaptive coupling gain for the controller is presented. Based on the Lyapunov function approach, the stability of the closed-loop system and the convergence of consensus errors are proved. Furthermore, the Zeno behavior is excluded for the triggering time sequences. Finally, simulation studies are given to verify the effectiveness of the proposed event-triggered fault-tolerant control scheme.

Output Feedback-Based Consensus for Nonlinear Multiagent Systems: The Event-Triggered Communication Strategy.

The current investigation explores the leader-following consensus problem for nonlinear multiagent systems under the output feedback control mechanism and the event-triggered communication mechanism. Owing to the physical instrument constraints, a significant portion of the state variables is not readily available. Therefore, this article put forward a distributed event-based leader-following consensus protocol only using agents' relative output measurements and underlying neighbors. Furthermore, this article develops two event-triggered mechanisms simultaneously, one is the event-triggered communication mechanism in the sensor-to-controller channel, and another is the event-triggered controller update in the controller-to-actuator track. Besides that, it is proven that the developed event-triggered control protocol can settle the leader-following consensus problem of the nonlinear multiagent systems, and the Zeno behavior is excluded in both the channels. Finally, we perform two simulation examples to illustrate the efficacy of the obtained results.

Resilient Consensus of Multiagent Systems Under Collusive Attacks on Communication Links.

This article addresses the resilient consensus problem of multiagent systems subject to cyber attacks on communication links, where the attacks on different links may collude to maintain undetectable. For the case with noncollusive attacks on links, a distributed fixed-time observer is designed so that the attack on each link can be detected by the two associated agents. A necessary and sufficient condition is derived to ensure the isolation of attacked links and no mistaken isolation of normal ones. For the case with collusive attacks on links, a novel attack isolation algorithm is proposed by constructing extra observers on the basis of the previous designed distributed fixed-time observer via sequentially removing the information associated with one of the links. Based on the isolation of the attacked links, a control algorithm is designed, and a necessary and sufficient condition is provided to achieve resilient consensus. Numerical examples corroborate the effectiveness of the proposed strategies.

Efficient decentralized optimization for edge-enabled smart manufacturing: A federated learning-based framework

The volume of industrial data of smart manufacturing is growing rapidly. Edge computing has emerged as an advanced technique that provides scalable resources for Industrial Internet of Things (IIoT) devices to analyze industrial data and enhance productivity. However, real-time and privacy-protecting data services are crucial for comprehensive decision-making, particularly utilizing machine learning in edge-enabled smart manufacturing. Therefore, how to optimize efficiently the data processing has become a critical concern for manufacturers seeking to upgrade the overall manufacturing operations. In this paper, we propose a decentralized federated learning-based framework to ensure the processing of industrial data in a low-latency and secure manner. Our solution designs the combination between edge nodes and IIoT devices as a global consensus problem with equilibrium constraints. Moreover, we adopt the distributed Alternating Direction Method of Multipliers (ADMM) algorithm to optimize the proposed data processing model, considering its advantages of decomposability and parallelism. To flexibly handle various types of industrial data, such as low-rank and high-dimensional data, we present two types of inexact ADMM algorithms to provide efficient model training services, respectively. Furthermore, an integrated optimization flow is designed for data processing in edge-enabled smart manufacturing. Finally, using industrial datasets from a thermal power plant for steam prediction case, we show that the presented inexact algorithms can decrease the response time by up to 17.2% and 58% respectively compared to other existing algorithms, respectively, while achieving the comparable level of statistical accuracy.

Fixed-time leader–follower consensus for second-order multi-agent systems: Variable exponent sliding mode control approach

This paper investigates the fixed-time leader–follower consensus (LFC) problem of second-order multi-agent systems (MASs) with bounded disturbance under directed interaction topology. First, a sliding mode manifold (SMM) with consensus errors–dependent variable exponential coefficient is given. Then, two sliding mode control (SMC) protocols are proposed. The proposed control protocols can eliminate the singularity, while guaranteeing the fixed-time reachability of the consensus errors to the sliding mode surface (SMS) and the fixed-time convergence of the consensus errors toward the origin along the SMS. Finally, the validity of the obtained methodology is confirmed by two simulation examples.