Switching Topologies Research Articles

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.

Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems With Switching Topologies

In this paper, the local consensus problem of nonlinear time-delay multi-agent systems with switching topologies via distributed saturated impulsive control is discussed and the maximum domain of attraction is well estimated. Specifically, we develop a new estimation approach that is quite distinct from the contractive invariant set to estimate the domain of attraction. Moreover, a novel composite impulsive-instant-dependent Lyapunov function is constructed and an improved convex hull representation with more slack variables is adopted to minimize the conservativeness. And then, some delay-independent sufficient criteria in the form of bilinear matrix inequalities that guarantee local consensus of nonlinear time-delay multi-agent systems are obtained by means of the Lyapunov-Razumikhin technique and proof by contradiction. Through appropriate transformation, some linear matrix inequalities-based optimization problems constrained by the proposed local consensus criteria are formulated, and the corresponding numerical solutions are solved by the Yalmip. Finally, a simulation example is given to confirm the validity and superiority of the proposed theoretical results.

Observer-Based Event-Triggered Iterative Learning Consensus for Locally Lipschitz Nonlinear MASs

This paper aims to realize the robust tracking for nonidentical locally Lipschitz nonlinear multiagent systems (MASs) with unmeasurable states, for which an observer-based distributed event-triggered iterative learning control (ILC) framework is proposed. With this framework, distributed state observers provide the indispensable state information for agents to learn to complete the task. An initial state learning strategy is implemented to relax consistent initial conditions, which can improve the learning accuracy. An event-triggering mechanism is designed to reduce the occupation of communication and computing resources during the iterative learning process of MASs. With locally Lipschitz nonlinearities and iteration-varying uncertainties caused by nonrepetitive initial states, the double-dynamics analysis (DDA) method is adopted to illustrate the convergence of the ILC process. By setting appropriate learning gains and constructing a quasi-globally Lipschitz condition via the DDA method, the robust convergence can be achieved for MASs in the presence of switching topologies. A numerical simulation is used to show the validity of the proposed framework.

Fixed time containment control of multi-agent system under multi-source mismatched disturbance

Aiming at the cooperative control problem of multi-agent system, the fixed-time containment control of general second-order multi-agent system under mismatched disturbances is studied. Firstly, the problem of multi-agent system fixed-time containment control in ideal state is analyzed, and a distributed control protocol based on variable structure control is proposed. Then, a nonlinear fixed-time disturbance observer is designed, aiming at the mismatched disturbance, and a fixed-time control protocol based on the nonlinear disturbance observer is proposed. Finally, the effectiveness of the proposed control protocol under switching topology and multi-source disturbance is verified by numerical simulation.

Prediction-based scaled consensus control for heterogeneous multi-agent systems under switching topologies

Prediction-based scaled consensus control for heterogeneous multi-agent systems under switching topologies

Structural controllability of multi‐agent systems with directed switching topologies

AbstractThis paper considers structural controllability of multi‐agent systems (MASs) with switching topologies, in which each interaction topology is modeled by a weighted digraph. Under the adopted relative protocol, the MASs with directed switching topologies are modeled by a switched system with parameter interdependence. The technique of linear parameterization, the graph theory, and so forth are applied to tackle the structural controllability of the switched system. A graph‐theoretic interpretation for structural controllability of the system is proposed. Examples with single leader and multiple leaders are presented to illustrate our work.

Finite-time synchronization for coupled neural networks with time-delay jumping coupling

The finite-time synchronization problem is studied for coupled neural networks (CNNs) with time-delay jumping coupling. Markovian switching topologies, imprecise delay models, uncertain parameters and the unavailable of topology modes are considered in this work. A mode-dependent delay with pre-known conditional probability is built to handle the imprecise delay model problem. A hidden Markov model with uncertain parameters is introduced to describe the mode mismatch problem, and an asynchronous controller is designed. Besides, a set of Bernoulli processes models the random packet dropouts during data communication. Based on Markovian switching topologies, mode-dependent delays, uncertain probabilities and packet dropout, a sufficient condition that guarantees the CNNs reach finite-time synchronization (FTS) is derived. Finally, a numerical example is derived to demonstrate the efficiency of the proposed synchronous technique.

Efficiency Analysis of Single-Phase Photovoltaic Transformer-less Inverters

This paper presents an efficiency analysis of five single-phase transformer-less inverters for photovoltaic applications (Full H-Bridge, Half H-Bridge, H5, HERIC and NPC inverters) implemented with different topologies of switches. Silicon (Si) and Silicon Carbide (SiC) diodes have been considered combined with two kinds of IGBTs. Simulation results have been obtained for each of the systems in different operating conditions by using PLECS software. Power losses and European Efficiency (EE) have been calculated for all the topologies by including the real characteristics of the switches in the thermal models provided by the software

Almost sure finite-time synchronization of Markov jump complex dynamical networks with asynchronous switching

The almost sure finite-time synchronization for Markovian jump complex dynamical networks (CDNs) with time-varying delay is studied. The designed controller is supposed to be asynchronous with the CDNs states. The existing almost sure synchronization result of networks is explored within a finite time interval. The sampled-data control approach is employed to improve the control precision. Some sufficient criteria are obtained under the definition of almost sure finite-time synchronization for the CDNs with Markovian switching topology. To determine the asynchronous controller gain, the linear matrix inequality-based conditions are proposed. Then, two examples are given to illustrate the effectiveness.

Couple-group consensus of heterogeneous nonlinear multi-agent systems with cooperative–competitive interactions and input saturation

Couple-group consensus of multi-agent systems with cooperative–competitive interactions and input saturation is studied under fixed and switching topologies based on pinning control and event-triggered control. First, for heterogeneous multi-agent systems consisting of first- and second-order agents, we propose two new distributed event-triggered control protocols, and the control protocols both enable the groups of agents to achieve the desired consensus state, which can effectively reduce the number of controller updates and save communication resources. Second, based on the Lyapunov stability theory, the sufficient conditions are established for the couple-group consensus of multi-agent systems. Meanwhile, Zeno behavior is excluded. Third, the effectiveness and feasibility of the control methods proposed in this paper are verified via some simulation examples.

Distributed Interval Observers with Switching Topology Design for Cyber-Physical Systems

In this paper, the distributed interval estimation problem for networked Cyber-Physical systems suffering from both disturbances and noise is investigated. In the distributed interval observers, there are some connected interval observers built for the corresponding subsystems. Then, due to the communication burden in Cyber-Physical systems, we consider the case where the communication among distributed interval observers is switching topology. A novel approach that combines L∞ methodology with reachable set analysis is proposed to design distributed interval observers. Finally, the performance of the proposed distributed interval observers with switching topology is verified through a simulation example.

Research on dual-mode switching of the new dual full-bridge topology of the beam supply

Research on dual-mode switching of the new dual full-bridge topology of the beam supply

Secure group consensus of nonlinear multi‐agent systems with multiple attacks under periodic event‐triggered control

SummaryIn this paper, the secure group consensus is investigated via periodic event‐triggered output feedback control for nonlinear multi‐agent systems subject to multiple attacks, where replay attacks and denial‐of‐service attacks are considered simultaneously. To avoid uninterrupted communication between agents, a novel fixed/switching continuous‐discrete compensator is first put forward by introducing a discrete‐time triggering mechanism in relative output signals. Then, with the help of the gain control technique, a compensator‐based periodic event‐triggered secure control protocol is established, which includes a triggering mechanism and an output feedback controller that both are discrete‐time. Particularly, Zeno behavior and continuous monitoring of the triggering function are naturally avoided compared with existing event‐triggered control protocols. Further, by combining the Lyapunov‐Krasovskii functional approach with switching topology theory, the secure group consensus is successfully achieved under the designed secure control protocol, meanwhile, the negative effect of multiple attacks on the system is compensated. Finally, two simulation examples are applied to verify the effectiveness of proposed control protocols.

Data-Driven Optimal Formation Control for Multiple Nonlinear Quadrotors With Switching Topologies

This paper addresses the optimal distributed formation control of multiple quadrotor vehicles under switching topologies, where each vehicle suffers from significant nonlinearity and uncertainty, simultaneously. A distributed observer is constructed to generate the trajectory references for each vehicle. An optimal leader-following formation control protocol is then developed through the reinforcement learning method from the sampled vehicle data. Simulation results from a multiple quadrotors example under switching topologies are presented to verify the obtained results.

Leader Selection in Impulsive Multiagent Systems With Switching Topologies.

In leader-follower multiagent systems (MASs), seeking an efficient scheme to select a set of agents as leaders is important for realizing the expected cooperative performance. In this article, the problem of minimal leader selection is investigated for impulsive general linear MASs with switching topologies. This study focuses on selecting a set of agents as leaders that receive information from a reference signal directly, while minimizing the number of leaders, subject to consensus tracking performance. First, adopting the average dwell time technique and a time-ratio constraint, an explicit criterion for consensus tracking is derived as prepreparation for leader selection. Second, applying the submodular optimization framework, leader selection metrics are established based on the derived criterion. Third, employing the greedy rule, an efficient leader selection scheme is presented according to the established metrics. The scheme comprises two polynomial-time algorithms that return selected leader sets within a logarithmic bound of the optimum. Finally, the effectiveness of the developed leader selection scheme is verified using an illustrative example.

Data-Driven H∞ Output Consensus for Heterogeneous Multiagent Systems Under Switching Topology via Reinforcement Learning.

In this article, a novel model-free policy gradient reinforcement learning algorithm is proposed to solve the H∞ tracking problem for discrete-time heterogeneous multiagent systems with external disturbances over switching topology. The dynamics of the followers and the leader are unknown, and the leader's information is missing for each agent due to the switching topology. Therefore, a distributed adaptive observer is introduced to learn the leader's dynamic model and estimate its state for each agent. For the H∞ tracking problem, an exponential discount value function is established and the related discrete-time game algebraic Riccati equation (DTGARE) is derived, which is the key to obtaining the control strategy. Furthermore, a data-based policy gradient algorithm is proposed to approximate the solution of the GAREs online and the utilization of agents' accurate knowledge is avoided. To improve the efficiency of data utilization, an offline dataset and the experience replay scheme are used. In addition, the lower bound of the exponential discount value is explored to ensure the stability of the systems. In the end, a simulation is provided to show the validity of the proposed method.

Distributed fixed-time control strategy for islanded microgrids considering perturbations and switching topologies

Distributed fixed-time control strategy for islanded microgrids considering perturbations and switching topologies

Consensus of Multiagent Systems With Time-Varying Delays and Switching Topologies Based on Delay-Product-Type Functionals.

This article investigates the consensus problem of multiagent systems (MASs) with time-varying delays subject to switching topologies. For the purpose of obtaining less conservative consensus conditions, first, a delay-product-type Lyapunov-Krasovskii functional (LKF) based on the auxiliary function-based integral inequality (AFBII) is constructed. Then, the generalized reciprocally convex matrix inequality (GRCMI) and a relaxed quadratic function negative-determination lemma are introduced to obtain the maximal-allowable upper bound of time-varying delays. Moreover, a proportional and derivative-like (PD-like) protocol is designed and the result is extended to the leader-following consensus of agents under Lipschitz nonlinear dynamics. Finally, two illustrative examples, including Chua's circuit, are given to demonstrate the advantages of the new consensus criteria.

A Novel Event-Triggered Bipartite Consensus for PDE-Based Multiagent Systems With Switching Topologies and Antagonistic Interactions.

Unlike the traditional studies on multiagent systems (MASs), this article investigates a class of MASs with spatial properties, whose agents are modeled by partial differential equations (PDE), in addition, to make the model more comprehensive, the Markovian switching topology with partially unknown probability is taken into account. The purpose of this article is to achieve the bipartite consensus for the above PDE-based MASs. In fact, the consideration of spatial factors in MASs will exacerbate the network transmission pressure, to overcome this problem, a novel spatiotemporal event-triggered mechanism is developed. Compared with the existing event-triggered mechanism, the proposed one is not only time-dependent but also covers the influence of spatial variables on the trigger conditions, which helps to further reduce the triggering frequency. Finally, three examples are given to verify the validity of the conclusion we proposed.