Observer‐based hybrid triggered control design for cluster synchronization of nonlinear complex dynamical networks

The issue of cluster synchronization and disturbance rejection of multi‐weighted complex dynamical networks subject to nonlinearities and external disturbances are studied in this article. In particular, a hybrid‐triggering control scheme is implemented to mitigate the burden of the network transmission according to the prespecified triggering condition, under which each node will transmit its signal independently to the controller. To be more specific, a Bernoulli distributed stochastic variable is introduced to describe the switching law of the communication scheme. Also, the disturbance rejection performance is carried out with the aid of an improved equivalent input disturbance estimator approach. The sufficient criterion in the form of linear matrix inequalities is derived by constructing a suitable Lyapunov–Krasovskii functional and employing stochastic theory. Based on these settings, the feedback gain matrices and the trigger parameters affirming the desired cluster synchronization performance of the considered networks are established. Eventually, two illustrative examples including Lur'e networks with simulations are presented, which evidently proves the effectiveness of the obtained results.

This paper investigates the synchronisation of nonlinear coupled complex dynamical networks with different nonlinear nodes and different orders by using decentralised dynamical compensation controllers. We propose a dynamical network mathematical model with similar nonlinear nodes, whose dimensions are different. For this kind of network model, the decentralised dynamical compensation controllers are designed for the state synchronisation of the coupled nodes. In addition, the synchronisation manifold is defined as an invariant manifold, which is regarded as the generalised case of dynamical networks with the same nodes’ dynamics. Furthermore, some stability criteria for the synchronisation are derived by means of rigorous theoretical analysis. Finally, numerical examples are presented to verify the effectiveness of the obtained theoretical results.

This paper concentrates on the cluster synchronization such that each community achieves linear-generalized synchronization in complex networks. Here two control schemes are introduced to realize cluster synchronization. One is to adjust the coupling strength of edges which connect different groups automatically, and to use the pinning control simultaneously. The other scheme is to adjust the coupling strength of edges in each group and to select only one node in each group to control. Finally, we present some simulations to demonstrate the correction of our conclusion.

Cluster synchronization of complex dynamic networks under pinning control via a limited capacity communication channel

This paper researched the stability and synchro-nization for the nonlinear coupled complex networks with a term of smooth nonlinear function, and its nodes have different dimensions. Because nodes in such complex networks contain similar behaviors, by defining the manifold of synchronization of the complex dynamical networks, a decentralized controllers with similar parameter characteristics and information is designed to ensure the synchronization of the system under the Lyapunov stability theorem. LMI based state feedback solution is proposed and upper bound of control function for guaranteed cost is figured out. Finally, the feasibility of the above theory is verified by numerical simulation.

Complex networks are everywhere.Synchronization is a very important nonlinear phenomenon which universally exists in nature.Over the last decade,many researchers have further investigated the synchronization of complex dynamical networks,including identical synchronzation,clustering synchronization,partial synchronization,and so on.The characterization of synchronous speed of complex dynamical networks in most known res(?)lts is asymptotic.That is,complex networks can realize synchronization only when the time t tends to infinity.However,there are few results reported on how long complex networks can reach synchronization.Based on two kinds of typical complex dynamical networks with nonlinear coupling,this paper will further explore the finite-time synchronization of complex dynamical networks.In detail,under some suitable conditions,it is proved that the above complex dynamical networks can realize accurate synchronization within finite- time.Moreover,a typical numerical simulation is then given to validate the effectiveness of the proposed criteria for finitetime synchronization.It should be especially pointed out that the finite-time synchronization sucessfully overcomes the difficulty of infinite synchronous time.The above results have some important practical meaning for the real-world engineering application.

In this article, the cluster synchronization control for a complex dynamic network (CDN) with mutually coupled nodes subsystem (NS) and connection relations subsystem is investigated. The process of cluster synchronization is segmented into three dynamic continuous stages: first, the free movement, then the task‐oriented clustering, and finally the cluster synchronization. The control scheme, founded on the clustering nodes of CDN, is proposed, such that the cluster synchronization arises when clustering all the nodes into two different sub‐networks (SNs). This approach originates from the flight motion for a group of autonomous aircrafts. At a certain moment, free flight is interrupted, and all the aircrafts split into two SNs according to the given clustering rules. Then the two controlled SNs are required to achieve cluster synchronization, that is, every SN converges to the same in speed. In order to split all the nodes into two different SNs, a clustering algorithm according to the “central nodes” is proposed. Based on Lyapunov stability theory, by designing the suitable inner cluster links, the adaptive controller of NS for each SN is synthesized to guarantee the stability of the error system. It is shown that the eventual inner topology of each SN is displayed in the pre‐given form when the cluster synchronization achieves. Finally, the merits and effectiveness of the proposed control scheme are verified by a simulation example.

The synchronization phenomenon is one of the crucial collective behaviors of the brain network, with its abnormal patterns in the brain networks of individuals with mental disorders like attention deficit hyperactivity disorder (ADHD) capturing the interest of researchers. ADHD is a prevalent disorder among children, which is linked to adverse outcomes such as impaired recognition of others' emotional facial expressions, leading to awkward social interactions. Despite numerous studies focusing on the synchronization analysis of brain networks in ADHD children while observing emotional facial expressions, the path to synchronization in these networks has been overlooked. For this reason, this research aims to investigate the differences in the synchronization transition of brain networks between healthy and ADHD children while processing emotional facial expressions based on their electroencephalogram signals. The analysis of synchronization cluster sequences in children's brain networks reveals that the formation and progression of synchronization clusters toward complete synchronization follow a more organized and goal-directed pattern in the healthy group than in the ADHD group. Furthermore, examining synchronization clusters with significant differences in stability (P-values < 0.05) during the clustering sequence between the two groups highlights abnormal synchronization in the frontal brain region during the early stages of neural processing in the ADHD group. This finding may contribute to deficits in attentional control and emotional regulation observed in ADHD children. Moreover, the classification results indicate the high potential of synchronization transition-based features to distinguish between ADHD and healthy children, with maximum accuracy, precision, and sensitivity of 82%, 77%, and 90%, respectively.

Exploring synchronizability of complex dynamical networks from edges perspective

This paper is devoted to the study of synchronization problems in uncertain dynamical networks with time-delayed nodes and coupling delays. First, a complex dynamical network model with time-delayed nodes and coupling delays is given. Second, for a complex dynamical network with known or unknown but bounded nonlinear couplings, an adaptive controller is designed, which can ensure that the state of a dynamical network asymptotically synchronizes at the individual node state locally or globally in an arbitrary specified network. Then, the Lyapunov-Krasovskii stability theory is employed to estimate the network coupling parameters. The main results provide sufficient conditions for synchronization under local or global circumstances, respectively. Finally, two typical examples are given, using the M-G system as the nodes of the ring dynamical network and second-order nodes in the dynamical network with time-varying communication delays and switching communication topologies, which illustrate the effectiveness of the proposed controller design methods.

Finite-time synchronization of complex dynamical networks under delayed impulsive effects

&lt;abstract&gt;&lt;p&gt;In this paper, cluster synchronization in finite/fixed time for semi-Markovian switching complex dynamical networks (CDNs) with discontinuous dynamic nodes is studied. Firstly, the global fixed-time convergence principle of nonlinear systems with semi-Markovian switching is developed. Secondly, the novel state-feedback controllers, which include discontinuous factors and integral terms, are designed to achieve the global stochastic finite/fixed-time cluster synchronization. In the framework of Filippov stochastic differential inclusion, the Lyapunov-Krasovskii functional approach, Takagi-Sugeno(T-S) fuzzy theory, stochastic analysis theory, and inequality analysis techniques are applied, and the global stochastic finite/fixed time synchronization conditions are proposed in the form of linear matrix inequalities (LMIs). Moreover, the upper bound of the stochastic settling time is explicitly proposed. In addition, the correlations among the obtained results are interpreted analytically. Finally, two numerical examples are given to illustrate the correctness of the theoretical results.&lt;/p&gt;&lt;/abstract&gt;

Complex dynamical networks consist of a large set of interconnected nodes with each node being a fundamental unit with detailed contents. A great number of natural and man-made complex networks such as social networks, food networks, neural networks, the World Wide Web, computer networks, electrical power grid and so on, can be effectively modelled by complex dynamical networks. Synchronization of a group of dynamical nodes in a complex network topology is one of the most interesting and significant phenomenon in complex dynamical networks. In this section, we shall discuss impulsive synchronization of the discrete delay networks. By employing the impulsive control method and the Razumikhin-type results obtained in previous chapter, two criteria for exponential synchronization will be derived.

Function projective synchronization in complex dynamical networks with time delay via hybrid feedback control

Delay-dependent [formula omitted] filtering for complex dynamical networks with time-varying delays in nonlinear function and network couplings