Finite-time H output synchronization for DCRDNNs with multiple delayed and adaptive output couplings.

This work concentrates on solving the finite-time H output synchronization (FTHOS) issue of directed coupled reaction-diffusion neural networks (DCRDNNs) with multiple delayed and adaptive output couplings in the presence of external disturbances. Based on the output information, an adaptive law to adjust output coupling weights and a controller are respectively developed to ensure that the DCRDNNs achieve FTHOS. Then, in the special case of no external disturbances, a corollary on the finite-time output synchronization (FTOS) of the DCRDNNs with multiple delayed and adaptive output couplings is provided.

Distributed optimization consensus for multi-agent systems on matrix-weighted networks.

In this paper, the distributed optimization consensus issues for both first-order continuous time (CT) and discrete-time (DT) multi-agent systems (MASs) on matrix-weighted networks are studied. In order to make each agent achieve optimization consensus, a new matrix-weighted distributed optimization algorithm for CT and DT MASs is proposed. Using the Lyapunov stability theory and matrix theory, the optimization consensus conditions are obtained, respectively.

Distributed adaptive robust containment control for reaction-diffusion neural networks with external disturbances under directed graphs.

In this paper, the leader-follower robust synchronization issue is mainly addressed for reaction-diffusion neural networks (RDNNs) with multiple leaders and external disturbances under directed graphs. Based on the σ modification approach, we propose a novel distributed adaptive controller by adding a term [Formula: see text] to avoid the phenomenon of parameter drift, that is, the adaptive parameters grow to infinity. Meanwhile, different from the adaptive control algorithm proposed in the undirected graph, we introduce a new function χ(t) to provide additional freedom for the design to achieve robust containment when confronted with external disturbances.

Controllability of N -Duplication Corona Product Networks With Laplacian Dynamics.

This article studies the controllability of a new composite network generated by two smaller scale factor networks via the Corona product with Laplacian dynamics. First, the eigenvalues and corresponding eigenvectors of a new composite network-the N -duplication Corona product network-are derived by some properties of its factor networks. Second, a necessary and sufficient algebra-based criterion for the controllability of such network is established based on the Popov-Belevitch-Hautus (PBH) test.

Transmission-Constrained Consensus Over Random Graphs.

The exchange of information is a crucial factor in achieving consensus among agents. However, in real-world scenarios, nonideal information sharing is prevalent due to complex environmental conditions. Consider the information distortions (data) and stochastic information flow (media) during state transmission both caused by physical constraints, a novel model of transmission-constrained consensus over random networks is proposed in this work.

Matrix-Weighted Consensus of Second-Order Discrete-Time Multiagent Systems.

In this article, we study the matrix-weighted consensus issues for second-order discrete-time multiagent systems on directed network topology. Under the designed matrix-weighted consensus algorithm, based on the eigenvalues of the Laplacian matrix, coupling gains, and discrete interval, we build some consensus conditions for reaching discrete-time consensus and deduce some simplified and straightforward consensus conditions for undirected network topology. Besides, for a given network topology, we theoretically analyze the influence of the coupling gains and discrete intervals on the consensus conditions of the network dynamics.

Consensus of Matrix-Weighted Hybrid Multiagent Systems.

As we all know, heterogeneity is a very important feature of multiagent systems (MASs). In this article, we examine the consensus control problems of matrix-weighted hybrid MASs, which contain discrete-time and continuous-time dynamic agents. Under fixed and switched undirected networks, three consensus algorithms are proposed for matrix-weighted hybrid MASs.

Finite-Time Output Synchronization of Multiple Weighted Reaction-Diffusion Neural Networks With Adaptive Output Couplings.

This article mainly considers the output synchronization (OS) problem of multiple weighted and adaptive output coupled reaction-diffusion neural networks (RDNNs) without and with coupling delays in finite time. Without coupling delays, an adaptive control law and an output feedback controller are, respectively, proposed to ensure that the multiple weighted and output coupled RDNNs are output synchronized and output synchronized in finite time. With coupling delays, an adaptive coupling weights control scheme and a novel feedback controller are put forward to make the multiple weighted RDNNs with output couplings achieve OS in finite time.

Distributed Observer-Based Leader-Follower Consensus of Multiple Euler-Lagrange Systems.

This article investigates the leader-follower consensus problem of multiple Euler-Lagrange (EL) systems, where each agent suffers uncertain external disturbances, and the communication links among agents experience faults. Besides, we consider a more general case that only a portion of followers can measure partial components of leader's output and access the dynamic information of leader. The main idea of solving the consensus problem in this article is proceeded in two steps.

Semiglobal Robust Consensus of General Linear MASs Subject to Input Saturation and Additive Perturbations.

This article considers the robust consensus problem of the general linear multiagent system (MAS) subject to both heterogeneous additive stable disturbances and input saturation. Distributed low gain feedback-based dynamic output feedback control protocols are proposed, which do not need the controller interaction. Algebraic Riccati equation and unified H controller design method are employed to design the output feedback control protocols.

Leader-follower controllability of signed networks.

This study addresses leader-follower controllability of signed multi-agent networks with fixed and switching interactions (topologies), respectively, where weighted edges between agents may be positive or negative. In other words, there exist cooperative interactions (corresponding to positive edges) and antagonistic interactions (corresponding to negative edges) between agents in the multi-agent networks depicted by signed graphs. The goal of this study is to find the criteria of controllability for signed multi-agent networks, that is, how exactly do cooperation and antagonism affect controllability? It is proven that the followers of multi-agent networks under structurally balanced conditions can be controlled to the desired states if the leaders are chosen from the same partitioned subset.

Finite-size scaling of geometric renormalization flows in complex networks.

Some characteristics of complex networks need to be derived from global knowledge of the network topologies, which challenges the practice for studying many large-scale real-world networks. Recently, the geometric renormalization technique has provided a good approximation framework to significantly reduce the size and complexity of a network while retaining its "slow" degrees of freedom. However, due to the finite-size effect of real networks, excessive renormalization iterations will eventually cause these important "slow" degrees of freedom to be filtered out.

Bipartite Consensus for Second-Order Multiagent Systems With Matrix-Weighted Signed Network.

The second-order scalar-weighted consensus problem of multiagent systems has been well explored. However, in some practical antagonistic interaction networks, the interdependencies of multidimensional states of the agents must be described by matrix coupling. In order to highlight the influence of matrix coupling in the antagonistic interaction network, we investigate the second-order matrix-weighted bipartite consensus problem on undirected structurally balanced signed networks.

Sampling-Based Event-Triggered Exponential Synchronization for Reaction-Diffusion Neural Networks.

In this article, the exponential synchronization control issue of reaction-diffusion neural networks (RDNNs) is mainly resolved by the sampling-based event-triggered scheme under Dirichlet boundary conditions. Based on the sampled state information, the event-triggered control protocol is updated only when the triggering condition is met, which effectively reduces the communication burden and saves energy. In addition, the proposed control algorithm is combined with sampled-data control, which can effectively avoid the Zeno phenomenon.

Finite-time bipartite synchronization of switched competitive neural networks with time delay via quantized control.

This article tackles the finite-time bipartite synchronization (FTBS) of coupled competitive neural networks (CNNs) with switching parameters and time delay. Quantized control is utilized to achieve the FTBS at a small control cost and with limited channel resources. Since the effects of the time delay and switching parameters, traditional finite-time techniques cannot be directly utilized to the FTBS.

Identification of Network Topology Variations Based on Spectral Entropy.

Based on the fact that the traditional probability distribution entropy describing a local feature of the system cannot effectively capture the global topology variations of the network, some indicators constructed by the network adjacency matrix and Laplacian matrix come into being. Specifically, these measures are based on the eigenvalues of the scaled Laplace matrix, the eigenvalues of the network communicability matrix, and the spectral entropy based on information diffusion that has been proposed recently, respectively. In this article, we systematically study the dependence of these measures on the topological structure of the network.

Finite-Time Synchronization of Markovian Coupled Neural Networks With Delays via Intermittent Quantized Control: Linear Programming Approach.

This article is devoted to investigating finite-time synchronization (FTS) for coupled neural networks (CNNs) with time-varying delays and Markovian jumping topologies by using an intermittent quantized controller. Due to the intermittent property, it is very hard to surmount the effects of time delays and ascertain the settling time. A new lemma with novel finite-time stability inequality is developed first.

Adaptive Bipartite Time-Varying Output Formation Control for Multiagent Systems on Signed Directed Graphs.

The issue of bipartite time-varying formation (BTVF) tracking for linear multiagent systems (MASs) with a leader of unknown input on signed digraphs is investigated. An adaptive nonsmooth protocol is taken in this article that utilizes only the local output feedback information among neighbors and, thus, can avoid employing the eigenvalue information of the Laplacian matrix of the graph. It is proven that if the interaction network of agents containing a spanning tree is structurally balanced, the BTVF tracking can be achieved with a leader of the bounded input via the proposed scheme.

Distributed Adaptive Output Feedback Consensus of Parabolic PDE Agents on Undirected Networks.

In this article, we investigate the distributed adaptive consensus problem of parabolic partial differential equation (PDE) agents by output feedback on undirected communication networks, in which two cases of no leader and leader-follower with a leader are taken into account. For the leaderless case, a novel distributed adaptive protocol, namely, the vertex-based protocol, is designed to achieve consensus by taking advantage of the relative output information of itself and its neighbors for any given undirected connected communication graph. For the case of leader-follower, a distributed continuous adaptive controller is put forward to converge the tracking error to a bounded domain by using the Lyapunov function, graph theory, and PDE theory.

Distributed Adaptive Containment Control for Coupled Reaction-Diffusion Neural Networks With Directed Topology.

In this article, we consider the problem of distributed adaptive leader-follower coordination of partial differential systems (i.e., reaction-diffusion neural networks, RDNNs) with directed communication topology in the case of multiple leaders.

Consensus-Based Distributed Reduced-Order Observer Design for LTI Systems.

In this article, we refocus on the distributed observer construction of a continuous-time linear time-invariant (LTI) system, which is called the target system, by using a network of observers to measure the output of the target system. Each observer can access only a part of the component information of the output of the target system, but the consensus-based communication among them can make it possible for each observer to estimate the full state vector of the target system asymptotically. The main objective of this article is to simplify the distributed reduced-order observer design for the LTI system on the basis of the consensus communication pattern.

Second-Order Consensus for Multiagent Systems With Switched Dynamics.

This article investigates the consensus control problem for second-order multiagent systems with switched dynamics, consisting of a continuous-time subsystem and a discrete-time subsystem. Under a fixed directed topology, two linear control protocols are proposed for achieving consensus. One is that two subsystems use different control inputs, where the continuous-time system uses continuous-time control, and the discrete-time system uses discrete-time control.

Some necessary and sufficient conditions for containment of second-order multi-agent systems with intermittent sampled data.

This paper comes up with two novel sampled data containment control protocols with intermittent communication for second-order multi-agent systems, where the intermittent communication is periodic. For the protocols with or without time delay, two necessary and sufficient conditions are obtained. In both cases, containment control can be implemented, where each follower can eventually reach the convex hull made up of multiple leaders.

Consensus of Continuous-Time Linear Multiagent Systems With Discrete Measurements.

This article concerns the robust consensus problem of continuous-time linear multiagent systems (MASs) with uncertainty and discrete-time measurement information, where the output measurement information is in the data-sampled form. Distributed output-feedback protocol with or without controller interaction is proposed for each agent. Specifically, the output-feedback protocol runs in continuous time with an output error correction term mixed with the discrete-time measurement information.

H∞ Control for Observer-Based Non-Negative Edge Consensus of Discrete-Time Networked Systems.

This article is concerned with observer-based non-negative edge-consensus (OBNNEC) problems of networked discrete-time systems with or without actuator saturation. An algorithm which only uses actual outputs of neighboring edges is proposed by means of an H control method and modified algebraic Riccati equation (MARE)-based technique. The observer matrix and feedback matrix are constructed by solving the MARE and linear matrix inequality (LMI), respectively.