State observer and state estimation method of complex dynamic network

A complex dynamic network and state observer technology, applied in data exchange network, digital transmission system, electrical components, etc., can solve the problem of noise in the transmission channel

Inactive Publication Date: 2013-06-05
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of existing complex dynamic network state estimation methods, aim at the important problem of transmission channel noise, and provide a state observer for complex dynamic networks and a state estimation

Method used

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  • State observer and state estimation method of complex dynamic network
  • State observer and state estimation method of complex dynamic network
  • State observer and state estimation method of complex dynamic network

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0093] Example 1: Scale-free dynamic network state estimation with 10 nodes:

[0094] (1) Scale-free dynamic network model

[0095] We use the Lorenz mixed system as the node dynamics to generate a scale-free dynamic network of 10 nodes

[0096] x · i 1 x · i 2 x · i 3 = Ax i + f ( x ...

example 2

[0113] Example 2: Small-world dynamic network state estimation with 10 nodes:

[0114] (1) Small-world dynamic network model

[0115] We use the Lorenz mixed system as node dynamics to generate a small-world dynamic network of 10 nodes

[0116] x · i 1 x · i 2 x · i 3 = Ax i + f ( x ...

example 3

[0133] Example 3: State estimation of biological neural network:

[0134] (1) Establish a biological neural network containing 10 neurons

[0135] In this step, we use the Hindmarsh-Rose (HR) model as the neurons of the biological neural network to establish the biological neural network

[0136] x · i = Ax i + f ( x i ) + Σ j = 1 N c ij Γ x j

[0137] the y i =Hx i

[0138] in

[0139] A = 0 - 1 - 1 ...

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Abstract

The invention discloses a state observer of a complex dynamic network. Signal transmission between a monitored network and the state observer can be influenced by channel noise, the noise is suppressed by an integral observer, integral modeling is conducted on measuring signals of the complex dynamic network, the measuring signals after integral serve as control signals of an estimator so as to build an observer model; a norm controlling gain design of the observer of the complex dynamic network is given according to Lyapunov stability theory and linear matrix inequality, the norm is expressed by the linear matrix inequality so as to estimate the state of the complex dynamic network efficiently. The invention further discloses a state estimation method of the complex dynamic network based on the state observer. According to the state observer and the state estimation method of the complex dynamic network, state errors can be restrained to a low-amplitude noise range, and therefore accurate estimation of all nodes in the complex dynamic network is achieved.

Description

technical field [0001] The invention relates to a state estimation method of a complex dynamic network, in particular to a state estimation method of a complex dynamic network under the condition that the communication between the monitored complex dynamic network and an observer is disturbed by noise. Background technique [0002] Complex dynamic networks are formed by information coupling between individuals with simple dynamic behaviors. Due to the mutual influence of dynamic behaviors between individuals, the dynamic behaviors of dynamic networks present complexity. Because this complex dynamic network model can describe many phenomena in nature and engineering, such as the dynamic behavior of coupled oscillators, flight teams during bird migration, power grids, connections between biological neurons, Internet, World Wide Web, etc. Therefore, the study of complex networks has become a new science in the 21st century. [0003] For large-scale complex networks, due to the...

Claims

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Application Information

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IPC IPC(8): H04L12/26
Inventor 樊春霞蒋国平顾瑜
Owner NANJING UNIV OF POSTS & TELECOMM
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