HYBRID PINNING CONTROL FOR COMPLEX NETWORKS

2012 ◽  
Vol 22 (10) ◽  
pp. 1250252 ◽  
Author(s):  
LUIZ FELIPE R. TURCI ◽  
ELBERT E. N. MACAU
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Chaos Control ◽  
Dynamical Behavior ◽  
Pinning Control ◽  
Synchronization Control ◽  
Network Nodes

In this work, we present two different hybrid pinning strategies to synchronize a complex network of identical agents into a known desired solution. The first strategy is the chaos control hybrid pinning in which pinning synchronization control and chaos control are merged. The second strategy is the nonidentical reference hybrid pinning, in which the pinning reference dynamical behavior is different from network nodes dynamical behavior.

Projective synchronization via adaptive pinning control for fractional-order complex network with time-varying coupling strength

2019 ◽  
Vol 30 (07) ◽  
pp. 1940013
Author(s):  
Darui Zhu ◽  
Rui Wang ◽  
Chongxin Liu ◽  
Jiandong Duan
Keyword(s):  
Complex Network ◽  
Fractional Order ◽  
Control Method ◽  
Pinning Control ◽  
Projective Synchronization ◽  
Synchronization Control ◽  
Order Complex ◽  
Selection Algorithm ◽  
Feedback Control Method ◽  
Simulation Results

This paper presents an adaptive projective pinning control method for fractional-order complex network. First, based on theories of complex network and fractional calculus, some preliminaries of mathematics are given. Then, an analysis is conducted on the adaptive projective pinning control theory for fractional-order complex network. Based on the projective synchronization control method and the combined adaptive pinning feedback control method, suitable projection synchronization scale factor, adaptive feedback controller and the node selection algorithm are designed to illustrate the synchronization for fractional-order hyperchaotic complex network. Simulation results show that all nodes are stabilized to equilibrium point. Theoretical analysis and simulation results demonstrate that the designed adaptive projective pinning controllers are efficient.

scholarly journals Identifying Super-Spreader Nodes in Complex Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yu-Hsiang Fu ◽  
Chung-Yuan Huang ◽  
Chuen-Tsai Sun
Keyword(s):  
Infectious Diseases ◽  
Complex Networks ◽  
Complex Network ◽  
Information Dissemination ◽  
Local Features ◽  
Disease Detection ◽  
Network Nodes ◽  
Global Diversity ◽  
High Betweenness ◽  
Influential Individuals

Identifying the most influential individuals spreading information or infectious diseases can assist or hinder information dissemination, product exposure, and contagious disease detection. Hub nodes, high betweenness nodes, high closeness nodes, and highk-shell nodes have been identified as good initial spreaders, but efforts to use node diversity within network structures to measure spreading ability are few. Here we describe a two-step framework that combines global diversity and local features to identify the most influential network nodes. Results from susceptible-infected-recovered epidemic simulations indicate that our proposed method performs well and stably in single initial spreader scenarios associated with various complex network datasets.

INFORMATION ASYMMETRY FLOWING IN COMPLEX NETWORKS

2012 ◽  
Vol 26 (31) ◽  
pp. 1250183
Author(s):  
CHEN-XI SHAO ◽  
HUI-LING DOU ◽  
BING-HONG WANG
Keyword(s):  
Symmetry Breaking ◽  
Complex Networks ◽  
Information Asymmetry ◽  
Complex Network ◽  
Information Flow ◽  
Weak Link ◽  
Network Evolution ◽  
Long Tail ◽  
Network Nodes ◽  
Concept Of Information

The concept of information asymmetry in complex networks is introduced on the basis of information asymmetry in economics and symmetry breaking. Information flowing between two nodes on a link is bidirectional, whose size is closely related to traffic dynamics on the network. Based on asymmetric information theory, we proposed information flow between network nodes is asymmetrical. We designed two methods to calculate the amount of information flow based on two mechanisms of complex network. Unequal flow of two opposite directions on the same link proved information asymmetry exists in the complex network. A complex network evolution model based on symmetry breaking is established, which is a truthful example for complex network mimicking nature. The evolution mechanism of symmetry breaking can best explain the phenomenon of the weak link and long tail theory in complex network.

scholarly journals Outer Synchronization of Complex Networks with Nondelayed and Time-Varying Delayed Couplings via Pinning Control or Impulsive Control

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwen Feng ◽  
Sa Sheng ◽  
Ze Tang ◽  
Yi Zhao
Keyword(s):  
Complex Networks ◽  
Impulsive Control ◽  
Sufficient Conditions ◽  
Pinning Control ◽  
Time Varying ◽  
Network Nodes ◽  
Outer Synchronization ◽  
Synchronization Problem ◽  
Response Network ◽  
Control Schemes

The outer synchronization problem between two complex networks with nondelayed and time-varying delayed couplings via two different control schemes, namely, pinning control and impulsive control, is considered. Firstly, by applying pinning control to a fraction of the network nodes and using a suitable Lyapunov function, we obtain some new and useful synchronization criteria, which guarantee the outer synchronization between two complex networks. Secondly, impulsive control is added to the nodes of corresponding response network. Based on the generalized inequality about time-varying delayed different equation, the sufficient conditions for outer synchronization are derived. Finally, some examples are presented to demonstrate the effectiveness and feasibility of the results obtained in this paper.

scholarly journals Learning Impulsive Pinning Control of Complex Networks

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2436
Author(s):  
Alma Y. Alanis ◽  
Daniel Ríos-Rivera ◽  
Edgar N. Sanchez ◽  
Oscar D. Sanchez
Keyword(s):  
Neural Network ◽  
Complex Networks ◽  
Complex Network ◽  
Discrete Time ◽  
Pinning Control ◽  
Rayleigh Quotient ◽  
Control Input ◽  
Linear Connections ◽  
Algebra Approach ◽  
Unknown Node

In this paper, we present an impulsive pinning control algorithm for discrete-time complex networks with different node dynamics, using a linear algebra approach and a neural network as an identifier, to synthesize a learning control law. The model of the complex network used in the analysis has unknown node self-dynamics, linear connections between nodes, where the impulsive dynamics add feedback control input only to the pinned nodes. The proposed controller consists of the linearization for the node dynamics and a reorder of the resulting quadratic Lyapunov function using the Rayleigh quotient. The learning part of the control is done with a discrete-time recurrent high order neural network used for identification of the pinned nodes, which is trained using an extended Kalman filter algorithm. A numerical simulation is included in order to illustrate the behavior of the system under the developed controller. For this simulation, a 20-node complex network with 5 different node dynamics is used. The node dynamics consists of discretized versions of well-known continuous chaotic attractors.

scholarly journals Adaptive Synchronization of Complex Networks with Mixed Probabilistic Coupling Delays via Pinning Control

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Jian-An Wang
Keyword(s):  
Complex Networks ◽  
Pinning Control ◽  
Adaptive Synchronization ◽  
Time Varying ◽  
Feedback Controllers ◽  
Adaptive Feedback ◽  
Network Nodes ◽  
Coupling Delay ◽  
Low Dimensional ◽  
Theoretical Results

The problem of synchronization for a class of complex networks with probabilistic time-varying coupling delay and distributed time-varying coupling delay (mixed probabilistic time-varying coupling delays) using pinning control is investigated in this paper. The coupling configuration matrices are not assumed to be symmetric or irreducible. By adding adaptive feedback controllers to a small fraction of network nodes, a low-dimensional pinning sufficient condition is obtained, which can guarantee that the network asymptotically synchronizes to a homogenous trajectory in mean square sense. Simultaneously, two simple pinning synchronization criteria are derived from the proposed condition. Numerical simulation is provided to verify the effectiveness of the theoretical results.

Equilibrium-pinning control for complex networks with inter-node coupling strength saturation improvement

2019 ◽  
Vol 31 (01) ◽  
pp. 2050013
Author(s):  
Chen Huang ◽  
Xinbiao Lu ◽  
Jun Zhou ◽  
Huimin Qian ◽  
Haoqian Huang ◽  
...  
Keyword(s):  
Complex Networks ◽  
Control Strategy ◽  
Coupling Strength ◽  
Pinning Control ◽  
Network Equilibrium ◽  
Node Number ◽  
Network Nodes ◽  
Numerical Examples ◽  
Practical Applications ◽  
Saturation Threshold

In most conventional complex network equilibrium-pinning control, all the network nodes are usually balanced by attaching at least one controller to each node of the concerned network. When the node number is huge and the inter-node connections are complex, this control strategy requires the ability to manipulate the inter-node coupling strength to grow rapidly and intensively. In practical applications, however, the inter-node coupling strength cannot be increased unlimitedly; as a matter of fact, the coupling strength cannot be further changed after reaching some saturation threshold. In this paper, by exploiting the improved coupling strength saturation function, we suggest a new pinning control strategy that makes the network reach its equilibrium-pinning point more effectively than the network with saturated coupling strength. Numerical examples are illustrated to show the effectiveness of the main results.

Synchronization of time-varying coupled complex networks via adaptive pinning control

2021 ◽  
pp. 2150164
Author(s):  
Hai Lin ◽  
Jincheng Wang
Keyword(s):  
Lyapunov Function ◽  
Complex Networks ◽  
Complex Network ◽  
Function Theory ◽  
Pinning Control ◽  
Time Varying ◽  
Control Parameters ◽  
State Variables ◽  
Network Time ◽  
Adaptive Coupling

Pinning synchronization of complex networks with two different kinds of time-varying coupling are studied in this paper. Inner coupling of the state variables and outer coupling in the complex network are taken into consideration. Based on the Lyapunov function theory, some general criteria and a simplified corollary for ensuring network synchronization are proposed. Linear pinning controllers, adaptive pinning controllers and adaptive coupling strength are designed for achieving complex network time-varying synchronization. Furthermore, the analytic relationship between control parameters is studied. Numerical simulations further illustrate the effectiveness of conclusions.

scholarly journals Recommended method study based on incorporating complex network ripple net

2021 ◽  
Vol 39 (5) ◽  
pp. 1070-1076
Author(s):  
Yutai LUO ◽  
Tao XU ◽  
Zhangbo XU
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Present Method ◽  
Network Models ◽  
User Preferences ◽  
Experimental Results ◽  
Knowledge Graph ◽  
Knowledge Maps ◽  
Network Nodes

The RippleNet network models user preferences and is well applied in the recommended system. But Ripplenet didn't take into account the weight of entities in the knowledge graph, resulting in the inaccurate recommendation results. A RippleNet model incorporating the influence of the complex network nodes is proposed. After constructing the complex networks based on the knowledge maps, the maximum subnet model is extracted, the influence of the nodes in the map network is calculated, and the weight of the nodes is added to the RippleNet model as an entity. The experimental results showed that the present method increased the AUC and ACC values of RippleNet to 92.0% and 84.6%, made up for the problem that no entity influence was considered in the RippleNet network, and made the recommended results more in line with users' expectations.

THE LOCAL STOCHASTIC STABILITY FOR COMPLEX NETWORKS UNDER PINNING CONTROL

2012 ◽  
Vol 22 (05) ◽  
pp. 1250113 ◽  
Author(s):  
ZHOU YAN ◽  
XIAO-LING JIN ◽  
ZHI-LONG HUANG
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Stochastic Stability ◽  
Pinning Control ◽  
Damping Coefficient ◽  
Largest Lyapunov Exponent ◽  
Stochastic Perturbations ◽  
The Matrix ◽  
Negative Damping ◽  
System Of Parameters

The local stochastic stability of complex networks under pinning control is studied, with stochastic perturbations to the coupling strengths. The nodes of complex network are modeled as second-order differential equations subject to stochastic parametric excitations. The complex network is first linearized at its trivial solution, and the resulting equations are reduced to independent subsystems by using a suitable linear transformation. Then the condition of the stochastic stability can be determined by Lyapunov exponents of the subsystems. The largest Lyapunov exponent of the subsystem can be expressed analytically, as a function of the eigenvalue of a matrix associated with the coupling matrix and pinning control matrix for a given system of parameters. And the stability region with respect to the eigenvalue can be obtained. It is pointed out that the local stochastic stability of the network is finally determined by the maximal and minimum eigenvalues of the matrix. Numerical results with positive and negative damping coefficients are given to illustrate the criterion. Moreover, for the positive damping coefficient case, the pinning control may destabilize the network; and for the negative damping coefficient case, the pinning control may stabilize the network.

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