Synchronisation of complex dynamical networks with different dynamics of nodes via decentralised dynamical compensation controllers

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.     

Stability analysis and decentralized control of a class of complex dynamical networks

In this paper, stability analysis and decentralized control problems are addressed for linear and sector-nonlinear complex dynamical networks. Necessary and sufficient conditions for stability and stabilizability under a special decentralized control strategy are given for linear networks. Especially, two types of linear regular networks, star-shaped networks and globally coupled networks, are studied in detail. A dynamical network is viewed as a large-scale system composing of some subsystems, based on which the relationship between the stability of a network and the stability of its corresponding subsystems is investigated. It is pointed out that some subsystems must be unstable for the whole network to be stable in some special cases. Moreover, a controller design method based on a parameter-dependent Lyapunov function is provided. Furthermore, interconnected Lur’e systems and symmetrical networks of Lur’e systems are similarly studied. The test of absolute stability of a network of Lur’e systems is separated into the test of absolute stability of several independent Lur’e systems. Finally, several numerical examples are given to illustrate the theoretical results.     

Stability analysis of dynamical neural networks

In this paper, we use the matrix measure technique to study the stability of dynamical neural networks. Testable conditions for global exponential stability of nonlinear dynamical systems and dynamical neural networks are given. It shows how a few well-known results can be unified and generalized in a straightforward way. Local exponential stability of a class of dynamical neural networks is also studied; we point out that the local exponential stability of any equilibrium point of dynamical neural networks is equivalent to the stability of the linearized system around that equilibrium point. From this, some well-known and new sufficient conditions for local exponential stability of neural networks are obtained     

Finite-time robust passive control for a class of switched reaction-diffusion stochastic complex dynamical networks with coupling delays and impulsive control

Finite-time boundedness and finite-time passivity for a class of switched stochastic complex dynamical networks (CDNs) with coupling delays, parameter uncertainties, reaction-diffusion term and impulsive control are studied. Novel finite-time synchronisation criteria are derived based on passivity theory. This paper proposes a CDN consisting of N linearly and diffusively coupled identical reaction- diffusion neural networks. By constructing of a suitable Lyapunov–Krasovskii's functional and utilisation of Jensen’s inequality and Wirtinger's inequality, new finite-time passivity criteria for the networks are established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, two interesting numerical examples are given to show the effectiveness of the theoretical results.     

Robust impulsive synchronization of linear discrete dynamical networks

This paper,aims to study robust impulsive synchronization problem for uncertain linear discrete dynamical network. For the discrete dynamical networks with unknown but bounded linear coupling, by introducing the concept of uniformly positive definite matrix functions,some robust impulsive controllers are designed,which ensure that the state of a discrete dynamical network globally asymptotically synchronizes with an arbitrarily assigned state of an isolate node of the network. This paper also investigates the synchronization problem where the network coupling fianctions are uncertain but bounded nonlinear functions.Finally, two examples are simulated to illustrate our results.     

Robust decentralized stabilization for a class of large-scale time-delay uncertain impulsive dynamical systems

The problem of robust decentralized stabilization for a class of large-scale, time delay, and uncertain impulsive dynamical systems is introduced and studied. Some explicit criteria of robust exponential stabilization in the large for such systems are established. A simple approach to designing a robust decentralized controller is presented. A numerical example is given for illustrating and interpreting the theoretical results.     

Synchronisation of complex dynamical networks with additive stochastic time-varying delays

In this letter, a class of complex dynamical networks with additive stochastic time-varying delays is investigated. Two kinds of delays in complex dynamical networks are taken into consideration, one is called the nodes-induced delay in this paper, and the other is the network-induced delay. Both of the delays are assumed to obey different stochastic distributions. By utilising a novel Lyapunov–Krasovskii functional and stochastic analysis techniques, a sufficient criterion is obtained in the form of linear matrix inequalities to ensure the synchronisation of the complex dynamical networks. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.     

Distributed robust adaptive control for a class of dynamical complex networks against imperfect communications

In this article, a robust tracking control problem of a class of dynamical complex networks is presented through a distributed adaptive approach. Uncertain network topology with unknown coupling strength, delayed and perturbed communications and external disturbances are considered, while the bounds of channel noises and coupling delays and disturbances are assumed to be unknown. Adaptation laws are proposed to estimate the network coupling strength and the upper and lower bounds of communication state errors and disturbances on-line. Based on the information from adaptive schemes, a class of distributed robust adaptive controllers is constructed to automatically compensate for the imperfect network and disturbance effects. Then, according to the Lyapunov stability theory, it is shown that the achievement of tracking for complex networks is effective on imperfect communications and disturbances. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of an F-18 aircraft.     

Pinning weighted complex networks with heterogeneous delays by a small number of feedback controllers

Weighted complex dynamical networks with heterogeneous delays in both continuous-time and discrete-time domains are controlled by applying local feedback injections to a small fraction of network nodes. Some generic stability criteria ensuring delay-independent stability are derived for such controlled networks in terms of linear matrix inequalities （LMIs）, which guarantee that by placing a small number of feedback controllers on some nodes the whole network can be pinned to some desired homogenous states. In some particular cases, a single controller can achieve the control objective. It is found that stabilization of such pinned networks is completely determined by the dynamics of the individual uncoupled node, the overall coupling strength, the inner-coupling matrix, and the smallest eigenvalue of the coupling and control matrix. Numerical simulations of a weighted network composing of a 3-dimensional nonlinear system are finally given for illustration and verification.     

Regulation of unknown nonlinear dynamical systems via dynamical neural networks

In this paper, we are dealing with the problem of regulating unknown nonlinear dynamical systems. First a dynamical neural network identifier is employed to perform black box identification and then a regular static feedback is developed to regulate the unknown system to zero. Not all the plant states are assumed to be available for measurement.A preliminary version of this paper has been presented at the IEEE Mediterranean Symposium on new directions in control theory and applications, Chania, Crete, Greece, June 1993.     

Global stabilisation for a class of nonlinear time-delay systems based on dynamical output feedback sliding mode control

In this article, global stabilisation for a class of nonlinear time-varying delay systems with mismatched uncertainty is considered. The bound on the uncertainty is nonlinear and involves time-delay. For this system, a dynamical compensator is first designed. A delay free sliding surface in the augmented space formed by the system output and the compensator state variables is proposed. The stability of the sliding mode dynamics, which include the time-delay effects, are analysed using the Lyapunov–Razumikhin approach. Then, a delay dependent sliding mode control is proposed such that the system can be driven to the sliding surface in finite time and maintain a sliding motion on it thereafter. Finally, a simulation is presented to illustrate the effectiveness of the obtained results.     

Improved results on synchronisation of delayed complex dynamical networks via sampled-data control

This paper focuses on the synchronisation problem of delayed complex dynamical networks via sampled-data control. A novel input-delay-dependent Lyapunov–Krasovskii functional (LKF) is constructed for the first time, which can make full use of the information on the input delay. To strengthen the combinations of the vectors in the resulting augmented vector, a new zero value equality is founded. Based on the input-delay-dependent LKF and zero value equality, synchronisation criteria are established. In comparison with some existing synchronisation criteria, the criteria in this paper are less conservative. The desired sampled-data controller is designed by solving a set of linear matrix inequalities. Finally, numerical examples are given to demonstrate the superiorities of proposed results.     

Geometric synthesis of a hybrid limit cycle for the stabilizing control of a class of nonlinear switched dynamical systems

This paper proposes a new constructive method for synthesizing a hybrid limit cycle for the stabilizing control of a class of switched dynamical systems in R², switching between two discrete modes and without state discontinuity. For each mode, the system is continuous, linear or nonlinear. This method is based on a geometric approach. The first part of this paper demonstrates a necessary and sufficient condition of the existence and stability of a hybrid limit cycle consisting of a sequence of two operating modes in R² which respects the technological constraints (minimum duration between two successive switchings, boundedness of the real valued state variables). It outlines the established method for reaching this hybrid limit cycle from an initial state, and then stabilizing it, taking into account the constraints on the continuous variables. This is then illustrated on a Buck electrical energy converter and a nonlinear switched system in R². The second part of the paper proposes and demonstrates an extension to Rⁿ for a class of systems, which is then illustrated on a nonlinear switched system in R³.     

On pinning synchronization of complex dynamical networks

There exist some fundamental and yet challenging problems in pinning control of complex networks: (1) What types of pinning schemes may be chosen for a given complex network to realize synchronization? (2) What kinds of controllers may be designed to ensure the network synchronization? (3) How large should the coupling strength be used in a given complex network to achieve synchronization? This paper addresses these technique questions. Surprisingly, it is found that a network under a typical framework can realize synchronization subject to any linear feedback pinning scheme by using adaptive tuning of the coupling strength. In addition, it is found that the nodes with low degrees should be pinned first when the coupling strength is small, which is contrary to the common view that the most-highly-connected nodes should be pinned first. Furthermore, it is interesting to find that the derived pinning condition with controllers given in a high-dimensional setting can be reduced to a low-dimensional condition without the pinning controllers involved. Finally, simulation examples of scale-free networks are given to verify the theoretical results.     

SIS model of epidemic spreading on dynamical networks with community

We present a new epidemic Susceptible-Infected-Susceptible (SIS) model to investigate the spreading behavior on networks with dynamical topology and community structure. Individuals in themodel are mobile agentswho are allowed to perform the inter-community (i.e., long-range) motion with the probability p. The mean-field theory is utilized to derive the critical threshold (λ _C ) of epidemic spreading inside separate communities and the influence of the long-range motion on the epidemic spreading. The results indicate that λ _C is only related with the population density within the community, and the long-range motion will make the original disease-free community become the endemic state. Large-scale numerical simulations also demonstrate the theoretical approximations based on our new epidemic model. The current model and analysis will help us to further understand the propagation behavior of real epidemics taking place on social networks.     

Fault-tolerant stabilisation in double-integrator networks

This article considers a network of agents with double-integrator internal dynamics, which share pieces of information on their position states. For such a system, a fault-tolerant decentralised stabilisation problem is addressed. The goal consists in placing the closed-loop poles in the open left-half of the complex plane, even in the presence of faults of the transmitting and receiving apparatuses of one or more agents. By exploiting some previous results on fault-tolerant control, a necessary and sufficient condition for the problem to admit a solution is proved. Further, an explicit formula is given for the local regulators, which can be taken of the first-order, actually the least one. Finally, the theory is extended to networks of agents with multiple-integrator internal dynamics.     

递归神经网络的结构研究

从非线性动态系统的角度出发,对递归动态网络结构及其功能进行详尽的综述。将递归动态网络分为三大类：全局反馈递归网络、前向递归网络和混合型网络。每一类网络又可分为若干种网络。给出了每种网络描述网络特性的结构图,同时还对多种网络进行了功能对比,分析了各种网络的异同。     

Robust control for a specific class of non-minimum phase dynamical networks

The problem of robust control of dynamic networks with non-minimum phase subsystems, where only scalar inputs and outputs are available for measurement, is solved. Conditions on the parameters of the network model and the control system are obtained that ensure that the control algorithm designed for minimum phase network systems remains valid for non-minimum phase network systems as well. Control of the dynamic network in the cases when it includes and does not include a master subsystems is considered. Examples of simulation are presented to illustrate the results.     

A unified synchronization criterion for impulsive dynamical networks

This paper focuses on the problem of globally exponential synchronization of impulsive dynamical networks. Two types of impulses are considered: synchronizing impulses and desynchronizing impulses. In previous literature, all of the results are devoted to investigating these two kinds of impulses separately. Thus a natural question arises: Is there any unified synchronization criterion which is simultaneously effective for synchronizing impulses and desynchronizing impulses? In this paper, a unified synchronization criterion is derived for directed impulsive dynamical networks by proposing a concept named “average impulsive interval”. The derived criterion is theoretically and numerically proved to be less conservative than existing results. Numerical examples including scale-free and small-world structures are given to show that our results are applicable to large-scale networks.