Switching Topologies Research Articles

Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks

This article investigates a Denial-of-Service (DoS) attack problem for nonlinear unknown discrete-time multiagent systems (MASs) to implement bipartite consensus tracking tasks with fixed and switching topologies. Firstly, an equivalent linearization data model of each agent is constructed using a pseudo partial derivative approach, where only one parameter needs to be estimated using input/output data of the controlled MASs. Meanwhile, the DoS attack behavior is described by a Bernoulli distribution process, and both cooperative and competitive relationships among agents are investigated. Moreover, an increment prediction compensator is designed to reduce the effect of DoS attacks. A data-based adaptive predictive bipartite consensus control algorithm is formulated. The corresponding theoretical analysis indicates that tracking errors of MASs with fixed and switching topologies converge to a small range around zero. Finally, several simulations and hardware tests further verify the proposed scheme’s effectiveness.

Collaborative communication-based ocean observation research with heterogeneous unmanned surface vessels

Unmanned surface vehicles (USVs) are crucial in ensuring maritime safety and observation, attracting widespread attention and research. However, a single USV exhibits limited performance and cannot effectively observe complex marine environments. In contrast, clusters of USVs can collaborate to execute complex maritime tasks, thereby enhancing the overall operational efficiency. USVs typically form heterogeneous clusters by combining vehicles with varying maneuverabilities and communication network capabilities. This has sparked an increased interest in cooperative communication research within heterogeneous USV clusters. The heterogeneous USVs discussed in this paper share the same dynamic model; however, they differ in dynamic parameters and communication capabilities. First, this study establishes a three-degree-of-freedom motion mathematical model for an underdriven USV considering environmental interference. It estimates the dynamic parameters of four USVs and evaluates their communication abilities, laying the foundation for researching the cooperative control of heterogeneous USV clusters and their application in Ocean Observation. Next, the communication capability of the USVs is assessed by studying the communication mode and signal transmission loss within the USV clusters. This study investigates the problem of cooperative communication in USV cluster formation, starting with the communication delay of USV clusters under a directed switching topology. Finally, a coherent formation controller is designed under a switching communication topology to address the dynamic transformation of communication topologies within heterogeneous USV clusters. This verifies that heterogeneous USV clusters can seamlessly form and maintain formation shapes during communication topology transformations through formation simulation experiments involving four heterogeneous USVs was 22% higher than that of dispersed control topology structures. This study provides a solid foundation for future investigations into the cooperative control of heterogeneous USV clusters and their applications in marine observations.

Topology Switch between AIE and ACQ: A Balance of Substituents

Topology Switch between AIE and ACQ: A Balance of Substituents

Observer‐based event‐triggered consensus control of nonlinear cyber‐physical systems under backlash‐like hysteresis and denial‐of‐service attacks

AbstractIn this article, we investigate the problem of event‐triggered distributed consensus control for a class of complex cyber‐physical systems (CPSs), where unknown backlash‐like hysteresis inputs and denial‐of‐service (DoS) attacks are considered in actuators and communication channels, respectively. In the first place, when communication networks are subjected to malicious DoS attacks, the connection weights of network communication topologies experience disruptions. To solve this issue, this work proposes a solution by constructing topological models for communication networks employing switching topologies and utilizing observers to estimate the combined measurement errors during the time interval of DoS attacks. Secondly, to address the repercussions of DoS attacks on control units and to optimize the utilization of communication resources, a distributed control protocol based on an event‐triggered scheme and employing locally deployed estimators is designed to significantly decrease the update frequency of control signals. Meanwhile, utilizing Lyapunov stability theory, the boundedness of all signals in the closed‐loop system is validated, thereby accomplishing the goal of consensus control. At last, the efficacy of the proposed control scheme is demonstrated through two simulation examples.

Practical fixed-time event-triggered output feedback containment control for second-order nonlinear multi-agent systems with switching topologies

This paper studies the fixed-time containment of the second-order nonlinear multi-agent system (MAS) accompanied by switching topologies and event-triggered communication. The agent is subjected to unknown nonlinear dynamics. A fixed-time RBF observer was constructed based on information obtained from neural networks and event-triggered communication. By combining the controller with the identification information from the observer, it is demonstrated that the system can achieve practical fixed-time output feedback containment and exclude Zeno behavior during the control process. The effectiveness of the proposed event-triggered control method for fixed-time output feedback containment control of the second-order nonlinear MAS is verified by simulation examples.

Fixed‐time Synchronization of Stochastic Kuramoto‐Oscillator Networks With Switching Topology Under Dynamic Event‐triggered Scheme

AbstractThis paper proposes a dynamic event‐triggered fixed‐time control scheme for the phase synchronization of Kuramoto networks with switching topology and stochastic coupling noise. To deal with the problems of switching topology and stochastic coupling noise, a multilayered control structure with a specially designed noise reduction layer is developed. The effectiveness is proved based on stochastic differential theory. To save communication resources and reduce control frequency, a dynamic event‐triggered mechanism is proposed. By introducing a dynamic variable into the triggering condition, the triggered instants are further reduced compared to the traditional static event‐triggered method. The synchronizing criteria and parameter conditions are established with stochastic Lyapunov stability theory. The analysis of Zeno behavior is also given. Finally, numerical simulation experiments are conducted to demonstrate the effectiveness of the proposed dynamic event‐triggered control scheme.

Fixed‐time sliding mode consensus tracking for second‐order nonlinear multi‐agent system with persistent dwell‐time switching topologies

AbstractThis article investigates the problem of fixed‐time sliding mode consensus tracking for nonlinear second‐order multi‐agent system, in the presence of disturbances and actuator attacks. The interaction topology graph of multi‐agent system is directed and switched, and the switching topologies satisfy a more general persistent dwell‐time switching mechanism. To account for the disturbances, actuator attack, and switching topologies, a nonsingular sliding mode control law with distributed switching scheme is constructed to guarantee the fixed‐time reachability to a sliding surface. By using multiple Lyapunov functions, some new sufficient criteria are derived for fixed‐time consensus tracking of the multi‐agent system with persistent dwell‐time switching topologies. To illustrate the proposed approach, we present a numerical example and a physical example of the single pendulum model.

Optimal leader-following consensus under switching topologies based on event-triggered NN-based observer

This paper proposes a novel control strategy for multi-agent systems (MASs) to achieve optimal leader-following consensus under jointly connected topologies. The devised approach incorporates two key components: an event-triggered neural network (NN)-based leader observer and an NN-based optimal controller. The proposed leader observer allows followers to locally reconstruct the leader’s dynamics, even in scenarios where the communication topology is jointly connected. The implementation of an event-triggered communication protocol significantly reduces the communication burden, enhancing the overall efficiency of information exchange. As the observer’s state converges to the actual leader’s state, the simplification of achieving leader-follower consensus becomes evident by directly setting the state of the leader observer as the tracking goal. An NN-based optimal controller is utilized to approximate the solution to the Hamilton–Jacobi–Bellman (HJB) equation, thus enabling optimal tracking of the leader by followers. Finally, the performance of the proposed control strategy is verified by simulations.

Optimal synchronization for multi-agent systems: A performance-dependent switching topology

This paper proposes an optimal output synchronization control method for heterogeneous multi-agent systems (HMASs) under a performance-dependent switching topology and DoS attacks. First, local and global switched performance index functions (SPIF) and SPIF-dependent topology switching law are proposed, respectively, thus, the control performance and topology quality can be quantitatively expressed. Second, an adaptive dynamic programming (ADP) algorithm with mode switching is proposed, aimed at dealing with the difficult Hamilton–Jacobi–Bellman equation, as well as the analytical complexity caused by the switching dynamics. The convergence of the switched ADP algorithm is proven to ensure its correct implementation. Then, for different topologies, multi-mode Actor–Critic neural networks (NNs) are built for each agent to calculate optimized control policies and SPIF, respectively. Furthermore, an NN-based state compensation mechanism is designed to expand the applicability of the designed switched ADP algorithm when the leader’s output transmission is unreliable. Finally, the results of numerical examples confirm that the proposed method is feasible.

Distributed time-varying optimization with coupled constraints: Application in UAV swarm predefined-time cooperative consensus

This paper addresses the global optimal consensus problem with time-varying objective functions and state-coupled inequality constraints. By integrating the predefined-time consensus and prediction-correction schemes, a distributed optimization protocol is proposed for the cooperative interception scenarios involving the unmanned aerial vehicle (UAV) swarm. Specifically, the δ-exact penalty method is utilized to eliminate the coupled constraints. A prediction-correction term with the penalty function is then established to track the trajectory of the time-varying optimal solution. Additionally, an edge-based predefined-time consensus term is introduced to facilitate the state consensus among UAVs. Under the undirected and connected topology, the proposed protocol ensures the predefined-time state consensus and asymptotically minimizes the sum of individual convex objective functions. Furthermore, the protocol is extended to other scenarios involving switching topology, directed detail-balanced topology, and external disturbances. Numerical simulations illustrate that the UAV swarm can form the predesigned interception formation with a predefined-time frame and effectively track the target swarm.

Practical finite‐time and fixed‐time multigroup consensus for second‐order nonlinear multi‐agent systems with Markov switching topology

AbstractPractical finite‐time and fixed‐time multigroup consensus questions for second‐order nonlinear multi‐agent systems (MASs) with Markov switching topologies are investigated in this article. Based on the topology of switching, each agent will appear to switch between different groups, and by setting up group switching signal variables embedded in error variables for each agent, finite‐time and fixed‐time control protocols are proposed, respectively, such that the conditions that must be satisfied for all agents to achieve practical finite‐time multigroup consensus and practical fixed‐time multigroup consensus can be obtained, respectively. For unknown nonlinear functions in the dynamical system, a radial basis function neural network (RBFNN) fit is used for approximation. Correspondingly, two examples are provided to verify the control effects of the control protocols.

Making Path Selection Bright: A Routing Algorithm for On-Chip Benes Networks

Making Path Selection Bright: A Routing Algorithm for On-Chip Benes Networks

Dynamic event‐triggered fixed‐time average consensus for general linear multi‐agent systems under switching topologies

AbstractThis article studies the practical fixed‐time average consensus problem of general linear multi‐agent systems under switching topologies. First, a distributed fixed‐time consensus control protocol based on dynamic event‐triggered mechanism is designed by using the local information exchange between neighboring agents. The protocol introduces an internal dynamic variable and the triggering condition changes in real time based on the dynamic variable obtained online, which can significantly reduce the number of triggering events and effectively decrease the energy consumption of the multi‐agent system. Then, the sufficient conditions for the multi‐agent system to solve the practical fixed‐time average consensus problem are given, and it is proved that there is no Zeno behavior in the system. Furthermore, a self‐triggered control scheme is proposed such that the neighboring agents communicate with each other only when one of them is triggered. In other words, this scheme does not require continuous communication between neighboring agents and thus reduces communication cost of the system. Finally, the simulation results verify the effectiveness of the proposed method.

Refined Dynamic Event-Triggering Cluster Consensus of Multiagent Systems With Fixed/Switching Topology.

This article is concerned with cluster consensus control of multiagent systems (MASs) with the fixed/switching topology under a dynamic event-trigger (DET) mechanism. A refined sampled-data-based DET scheme is proposed by introducing two dynamically adjusting threshold parameters to distinguish the different transmission requirements for neighboring agents intra and outer cluster. Faced with the difficulties of acquiring full state information among spatially distributed agents, output feedback is employed to construct cooperative control protocols. Both fixed and switching topologies are considered to execute the designed DET-based cooperative cluster consensus control protocols. By constructing appropriate Lyapunov-Krasovskii functionals (LKFs), some sufficient criteria in terms of matrix inequalities for the cluster consensus of MASs are derived, which can ensure that the error system with the proposed DET-based control strategy is asymptotically stable. Facing the nonconvex issue induced by output feedback, a particle swarm optimization (PSO)-based control design algorithm is novelly developed to calculate the control gains and event-triggering parameters jointly based on the derived stability criteria. The elements of the matrix variables are valued stochastically in certain ranges and the fitness function is designed as the accumulation of the weighting value of each matrix inequality. Finally, an application of multiple satellites formation flying is applied to numerically illustrate the effectiveness of the cluster consensus control strategy with the designed DET mechanism.

Reachable Set Estimation of Multiagent Systems: An Approximate Consensus Perspective

This paper is concerned with the estimation of reachable set for leaderless multi-agent systems (MASs) under fixed topology with bounded disturbances and nonzero initial conditions. In-neighbors' information is collected to design the protocol such that all agents' state trajectories are constrained within a compact set, and asymptotic consistency is regulated for disturbance-free MASs in the exponential stability sense while approximate consistency is regulated for noise-disturbed MASs in the input-to-state stability sense. The agreement dynamics are characterized by the consensus function with determined initial condition, whose estimated reachable set has non-empty intersection with that of MAS. The analytical framework is also applied to Markovian topology switching subject to completely and partially known transition rates, respectively. Numerical simulations confirm the theoretical results.

Consensus of multi-agent systems with randomly occurring nonlinearities via uncertain pinning control under switching topologies

This paper is focused on the consensus problem of multi-agent systems via uncertain pinning control under switching topologies. The stochastic disturbances and randomly occurring nonlinearities are proposed to describe more realistic systems. The communication topology is modeled by a directed graph and it is divided into two cases, the consensus problem is discussed in these two cases. In addition, there exist some uncertain pinning connections between the followers and leader due to switching topologies, the distributed control protocol is designed to satisfy the follower asymptotically converge to the leader. By constructing suitable multiple Lyapunov functions and utilizing tools of M-matrix theory, some sufficient consensus criteria are deduced to reach this goal. Finally, two examples are given to verify the correctness of the proposed method.

A refined adaptive event-based resilient filtering for complex networks over switching topology

The problem of the resilient filtering for a class of discrete-time complex networks over switching topology is investigated. Taking into account the limitation of channel bandwidth, a refined adaptive event-triggered scheme is derived, whose threshold is determined by the change rate of measurement. The large change rate of measurement results in a smaller threshold, which means that more data packets will be transmitted to guarantee the performance of filtering, and the smaller one leads to a bigger threshold to save the network energy. Under the adaptive event-triggered scheme, considering the switching topology and uncertain inner coupling, a resilient filtering with a variable filtering gain is proposed. Additionally, the minimal upper bound of the covariance of estimation error is developed and the sufficient conditions are also given to obtain the exponentially bounded in mean square of the estimation error system. Finally, a simulation is presented to certify the effectiveness of the derived resilient filtering.

Bipartite Formation Control of Nonlinear Multi-Agent Systems with Fixed and Switching Topologies under Aperiodic DoS Attacks

This paper concentrates on bipartite formation control for nonlinear leader-following multi-agent systems (MASs) with fixed and switching topologies under aperiodic Denial-of-Service (DoS) attacks. Firstly, distributed control protocols are proposed under the aperiodic DoS attacks based on fixed and switching topologies. Then, considering control gains, as well as attack frequency and attack length ratio of the aperiodic DoS attacks, using algebraic graph theory and the Lyapunov stability method, some criteria are acquired to ensure that the nonlinear leader-following MASs with either fixed or switching topologies can realize bipartite formation under aperiodic DoS attacks. Finally, numerical simulations are carried out to validate the correctness of the theoretical results.

Impulsive bounded consensus of two-layer multi-agent networks under deception attacks

This paper investigates the mean-square bounded consensus issue in a two-layer multi-agent network under deception attacks. The two-layer network is composed of the leader and follower layers with a switching topology. Employing an impulsive control method, the mean-square bounded consensus for the leader layer and the node-to-node mean-square bounded consensus of the two-layer network are analyzed. Based on the knowledge of graph theory, Lyapunov stability theory, and linear matrix inequalities, sufficient conditions for the mean-square bounded consensus of multi-agent systems in the two-layer network are derived. Finally, the practicability and efficacy of the theoretical outcomes are corroborated via the provided numerical simulations.

Event-triggered and stochastic-sampled consensus of nonlinear multi-agent systems under semi-Markov switching topology

This article investigates exponential mean square consensus (MSC) problem of leader–follower multi-agent systems (MASs). It is considered that the communication topology switches randomly and obeys a semi-Markov process. In view of possible data loss in information transmission, stochastic sampling scheme is introduced. Meanwhile, mode-dependent event-triggered control strategy based on sampled data is adopted to decrease communication broadband. The two cases that the transition rate matrix (TRM) of semi-Markov process is completely or partially known are respectively discussed. As a result, several sufficient conditions which can ensure to achieve exponential MSC are respectively deduced by means of stochastic Lyapunov theory and linear matrix inequality (LMI) theory. At last, two simulation tests corresponding to completely and partially known TRMs are designed to verify the correctness of the obtained conclusions.