Switching Topologies Research Articles

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

Relative States-Based Consensus for Sampled-Data Second-Order Multiagent Systems With Time-Varying Topology and Delays.

In this article, the consensus problem of sampled-data second-order integrator multiagent systems with switching topology and time-varying delay is studied. And, a zero rendezvous speed is not required in the problem. Two new consensus protocols that employ no absolute states are proposed, depending on the presence of delay. Sufficient synchronization conditions are obtained for both protocols. It is shown that consensus can be reached, provided there is a sufficiently small gain and periodically joint connectivity in the sense of scrambling graph or spanning tree. Finally, both numerical and practical examples are supplied for illustrative purpose, and both show the effectiveness of the theoretical results.

Fuzzy tracking control of singular multi-agent systems under switching topology

<p>The consensus tracking problem of leader-follower multi-agent systems (MASs) with singular structures on jointly connected topology is studied in this paper. To achieve the objective of consensus tracking, a distributed adaptive control protocol is formulated to adjust the coupling weights among the agents using the adaptive rate, where the adaptive protocol can be implemented by each agent in a fully distributed manner without using any global information. A fuzzy logic system method is used to deal with the nonlinear terms in response to the limitations of nonlinear system analysis. The consensus tracking problem is transformed into an error system stability analysis, and two sufficient conditions are provided to guarantee the control objective based on Lyapunov stability theory and singular system theory. Finally, the effectiveness of this method is verified through a simulation example.</p>

A leader-following consensus of multi-agent systems with actuator saturation and semi-Markov switching topologies.

The leader-following consensus (LFC) issue is investigated in this paper for multi-agent systems (MASs) subject to actuator saturation with semi-Markov switching topologies (SMST). A new consensus protocol is proposed by using a semi-Markov process to model the switching of network topologies. Compared to the traditional Markov switching topologies, the SMST is more general and practical because the transition rates are time-varying. By using the local sector conditions and a suitable Lyapunov-Krasovskii functional, some sufficient conditions are proposed such that the leaderfollowing mean-square consensus is locally achieved. Based on the derived sufficient conditions, an optimization problem is analyzed to determine the consensus feedback gains and to find a maximal estimate of the domain of consensus attraction (DOCA) of a closed-loop model. At the end, a numerical case is presented to verify the performance of the design method.

Research on the Synchronization Control of Fractional-Order Complex Networks Based on Switching Topology

Abstract: In the contemporary epoch, bolstered by information technology, the quintessence of networks is ubiquitously manifested, with a plethora of network types—ranging from the Internet, vehicular traffic frameworks, electrical distribution systems, cellular communication matrices, to social interconnection webs—being intricately woven into the fabric of societal functionality and quotidian existence. The domain of complex networks has burgeoned into a fervently pursued research vector, magnetizing an eclectic cohort of investigators from disciplines as variegated as mathematics, biosciences, and engineering. Notably, the fractional calculus has eclipsed its integer-order counterpart by offering enhanced precision in the depiction of real-world systems and phenomena. Consequently, the infusion of fractional calculus into the modeling of complex networks, to dissect their dynamic attributes and attendant control paradigms, has crystallized as a research nexus of burgeoning interest, eliciting scholarly discourse at both national and international echelons. [Purpose] This inquiry into the synchronization control of fractional-order complex networks, predicated on switching topology, endeavors to harness said topology as a scaffold for probing the synchronicity inherent within fractional-order complex networks. The objective is to augment the operational efficacy of these networks, broaden their sphere of applicability, and fortify the synchronal linkage amongst fractional-order complex networks and their counterparts. [Method] Predominantly, this exploration is underpinned by a synthesis of bibliographic scrutiny and analytical modeling, employing an extensive compendium of model equations to elucidate the subject matter. The spotlight is cast upon the Caputo fractional-order differential equation, with a focus on assaying the stability traits of its equilibrium junctures and formulating more expansive and pragmatic conditions for stability. In addition, to facilitate the precise estimation of elusive topologies within complex networks, a supplementary network—comprising isolated nodes and a regulatory protocol—is conceptualized. [Results] The findings suggest that the investigation into synchronization control based on switching topology propels the advancement of fractional-order complex networks and has substantial reference value. It serves to substantiate, to a certain degree, the postulations of antecedent theorists and chart a trajectory for ensuing scholarly endeavors in cognate domains, thereby perpetually amplifying the pragmatic utility of fractional-order complex networks.

Time-varying group formation tracking for nonlinear multi-agent systems under switching topologies

Time-varying group formation tracking for nonlinear multi-agent systems under switching topologies

Dynamic Optimal Formation Control for Mobile Vehicles With Minimizing Communication Path Loss Under Topology Switching

Dynamic Optimal Formation Control for Mobile Vehicles With Minimizing Communication Path Loss Under Topology Switching

Distributed Collaboration in Multimanipulator Systems With Switching and Weight-Unbalanced Topologies

Distributed Collaboration in Multimanipulator Systems With Switching and Weight-Unbalanced Topologies

Distributed Observer Design Over Directed Switching Topologies

Distributed Observer Design Over Directed Switching Topologies

Data-based bipartite formation control for multi-agent systems with communication constraints.

This article investigates data-driven distributed bipartite formation issues for discrete-time multi-agent systems with communication constraints. We propose a quantized data-driven distributed bipartite formation control approach based on the plant's quantized and saturated information. Moreover, compared with existing results, we consider both the fixed and switching topologies of multi-agent systems with the cooperative-competitive interactions. We establish a time-varying linear data model for each agent by utilizing the dynamic linearization method. Then, using the incomplete input and output data of each agent and its neighbors, we construct the proposed quantized data-driven distributed bipartite formation control scheme without employing any dynamics information of multi-agent systems. We strictly prove the convergence of the proposed algorithm, where the proposed approach can ensure that the bipartite formation tracking errors converge to the origin, even though the communication topology of multi-agent systems is time-varying switching. Finally, simulation and hardware tests demonstrate the effectiveness of the proposed scheme.

Hybrid Optimization Based Harmonic Minimization in Three Phase Multilevel Inverter With Reduced Switch Topology

Hybrid Optimization Based Harmonic Minimization in Three Phase Multilevel Inverter With Reduced Switch Topology

$ H_\infty $ deployment of nonlinear multi-agent systems with Markov switching topologies over a finite-time interval based on T–S fuzzy PDE control

<abstract><p>The deployment of multi-agent systems (MASs) is widely used in the fields of unmanned agricultural machineries, unmanned aerial vehicles, intelligent transportation, etc. To make up for the defect that the existing PDE-based results are overly idealistic in terms of system models and control strategies, we study the PDE-based deployment of clustered nonlinear first-order and second-order MASs over a finite-time interval (FTI). By designing special communication protocols, the collective dynamics of numerous agents are modeled by simple fist-order and second-order PDEs. Two practical factors, external disturbance and Markov switching topology, are considered in this paper to better match actual situations. Besides, T–S fuzzy technology is used to approximate the unknown nonlinearity of MASs. Then, by using boundary control scheme with collocated measurements, two theorems are obtained to ensure the finite-time $ H_\infty $ deployment of first-order and second-order agents, respectively. Finally, numerical examples are provided to illustrate the effectiveness of the proposed approaches.</p></abstract>

Dynamic Event-Triggered Consensus of Nonlinear Lur’e Networks With Directed Switching Topologies

Dynamic Event-Triggered Consensus of Nonlinear Lur’e Networks With Directed Switching Topologies

Secure Consensus Control of Multiagent Systems Under DoS Attacks: A Switching-Scheme-Based Active Defense Method.

This article studies the secure consensus control problem of multiagent systems (MASs) with a nonzero input leader subject to denial-of-service (DoS) attacks. The introduction of backup topologies makes it possible for MASs to actively defend against DoS attacks. Subsequently, a novel active defense method consisting of two types of state observers, an adaptive topology switching mechanism, and switching controllers is proposed, which can ensure the leader-follower bound consensus even if DoS attacks hinder the interaction between agents. Within such a defense framework, the switching mechanism, driven by the predefined performance index and designed monitoring function, can automatically search for a healthy communication graph among backup topologies. Concurrently, the observer-based switching control strategy will be modified to match the corresponding topology, in which the universal observer and controller parameters in different topologies are obtained by solving linear matrix inequalities. It should be highlighted that the developed defense scheme not only removes the limitations of existing results on the duration and frequency of DoS attacks but also ensures the same upper bound of consensus error before and after DoS attacks. Finally, several simulation examples for different systems illustrate the efficiency and superiority of the theoretical results.

Adaptive Neural Consensus of Unknown Non-Linear Multi-Agent Systems with Communication Noises under Markov Switching Topologies

In this paper, the adaptive consensus problem of unknown non-linear multi-agent systems (MAs) with communication noises under Markov switching topologies is studied. Based on the adaptive control theory, a novel distributed control protocol for non-linear multi-agent systems is designed. It consists of the local interfered relative information and the estimation of the unknown dynamic. The Radial Basis Function networks (RBFNNs) approximate the nonlinear dynamic, and the estimated weight matrix is updated by utilizing the measurable state information. Then, using the stochastic Lyapunov analysis method, conditions for attaining consensus are derived on the consensus gain and the weight of RBFNNs. The main findings of this paper are as follows: the consensus control of multi-agent systems under more complicated and practical circumstances, including unknown nonlinear dynamic, Markov switching topologies and communication noises, is discussed; the nonlinear dynamic is approximated based on the RBFNNs and the local interfered relative information; the consensus gain k must to be small to guarantee the consensus performance; and the proposed algorithm is validated by the numerical simulations finally.

Practical finite-time and fixed-time containment for second-order nonlinear multi-agent systems with IDAs and Markov switching topology

In this article, the finite-time containment problem and the fixed-time containment problem accompanied by injection and deception attacks (IDAs) and Markov switching topology for second-order nonlinear multi-agent systems (MASs) are investigated, respectively. By introducing a radial basis function neural network (RBFNN), the approximation property of radial basis neural networks is used to solve the unmeasurable difficulties of nonlinear functions and injection attacks. Finite-time and fixed-time distributed control protocols are proposed for switching topologies and attack-induced state deception and control injection, and finite-time and fixed-time containment as well as obtaining their corresponding sufficient conditions are achieved, respectively. Correspondingly, two examples are shown to demonstrate the feasibility of the control protocols.

Temperature field optimization for distributed combined heat of multi-microwave sources based on group consistency under time-varying communication topology

Microwave heating is one of the commonly used methods for heat treatment of various materials. This paper proposes a consistent variable power heating strategy under multi microwave source cluster switching topology mode. Firstly, a distributed structure of microwave source cluster collaborative output with bidirectional ring communication topology was constructed using virtual structure method. On this basis, nonlinear distributed control with consistent output of microwave source clusters in different modes was achieved. Meanwhile, a microwave source clustering scheme is proposed, and the objective function of automatic power allocation for each subgroup and its constraint function are constructed to realize the formation of different clustering modes in different time periods, and the consistent output of self-allocation of power for each subgroup. Secondly, the feasibility and effectiveness of the proposed strategy are verified by the experiments of heating SiC materials in a high-power microwave reactor and analyzing the temperature uniformity and energy conversion efficiency during the heating process. Finally, the simulation results show that the temperature uniformity is improved by 35.7%–63.6% and the energy conversion efficiency is improved by 27.9%–41.1%, which can effectively optimize the temperature field distribution.

Adaptive dynamic event-triggered cluster consensus for second-order delayed MASs with input saturation

In this paper, the cluster consensus problem of second-order multi-agent systems (SOMASs) is investigated in which cooperative-competitive interactions among agents, input time delay, and input saturation are involved simultaneously. A novel adaptive dynamic event-triggered control (ETC) protocol is first designed to realize cluster consensus. Since the constant in static trigger condition is replaced by a dynamic parameter, the new control scheme can reduce the trigger times and save energy consumption. Then, switching topology problem of heterogeneous multi-agent systems (MASs) is also discussed based on the dynamic ETC strategy. Some sufficient conditions for achieving the cluster consensus of SOMASs are proposed by utilizing the Lyapunov stability theory and algebraic graph theory. Especially, to solve the saturation problem, Lagrange mean value theorem is adopted. Moreover, it is also proved that no Zeno behavior occurs under the proposed control protocol. Finally, two examples justify the significance of our theoretical results.

Neural adaptive predefined-time formation tracking control of multiple Euler–Lagrange systems with switching topologies based on hierarchical mechanism

This paper investigates the event-triggered neural adaptive predefined-time time-varying formation tracking control (PTTVFTC) problem for multiple Euler–Lagrange systems (ELSs) with actuator failures and saturation under switching communication topologies. The hierarchical control mechanism (HCM) is employed to overcome the difficulties posed by switching communication topologies to design the control algorithms. Specifically, a new estimator is first developed in the estimator layer for each follower, which can estimate the leader’s position information within a predefined time. Then, based on the designed estimator, a fault-tolerant and anti-saturation controller is proposed in the local control layer for each follower, which enables each follower to achieve PTTVFTC. To reduce the communication frequency, an event-triggered mechanism (ETM) that does not have Zeno behavior determines the controller’s update. In addition, the settling time for formation tracking can be arbitrarily specified as desired. Finally, the effectiveness of the developed control strategy is verified by a simulation experiment.

Semi-global asymptotic state agreement of nonlinear multi-agent systems with communication delays under directed switching topologies

This paper investigates the semi-global state agreement problem for continuous-time nonlinear multi-agent systems with communication delays under direct and switching topologies. A systematic solution to the semi-global state agreement is presented and based on which a sufficient and necessary condition on the control laws is obtained, as long as the direct and switching communication topologies satisfy a mild joint connectivity assumption. Illustrative simulations are provided to validate the efficacy of the proposed theoretical results.