隨機與不確定因素下復(fù)雜網(wǎng)絡(luò)控制與同步研究

1、華中科技大學(xué)碩士學(xué)位論文隨機與不確定因素下復(fù)雜網(wǎng)絡(luò)控制與同步研究姓名：郭麗琳申請學(xué)位級別：碩士專業(yè)：控制理論與控制工程指導(dǎo)教師：王燕舞20090527華 中 科 技 大 學(xué) 碩 士 學(xué) 位 論 文 華 中 科 技 大 學(xué) 碩 士 學(xué) 位 論 文 Abstract Control and Synchronization of complex dynamical networks with stochastic and uncertain

2、 factors is one of the most famous problems in the world. In the real world, because of existence of the structure error, the influence caused by the change of the environment temperature and humidity and the random fact

3、or in information traffic, the stochastic and uncertain factors of complex dynamical network exist, and can not ignored sometimes. Therefore, it is necessary to build stochastic or uncertain complex dynamical network mod

4、el with low conservative property and change the analysis methods and tools according to the change of the model. Accordingly, the control and synchronization of complex dynamic networks with stochastic and uncertain fac

5、tors are analyzed, which is meaningful for the understanding and application of complex networks. Based on liner matrix inequality, undirected discrete Markovian time-dependent delay dynamical network model has been rese

6、arched by using descriptor system approach combining with variable transformation method. The sufficient condition for the stability of undirected discrete Markovian time-dependent delay network can be obtained. A contin

7、uous Markov jump delay network dynamical model is introduced, which consists of Markov jump mode-dependent delays and parameters. The stability and synchronization have been analyzed by using descriptor system approach a

8、nd the sufficient condition of the stability of continues-time Markov jump delay network can be obtained. Another continuous Markov jump delay network dynamical model is presented, namely, parameters, delays and inside c

9、oupling matrix are all subjected to Markov jump. Combining the property of Kronecker product with the Lyapunov functional, the sufficient condition of exponential mean square synchronization of continues-time Markov jump

10、 delay dynamical network can be obtained. The synchronization problem of time-varying delay network with stochastic nonlinear coupling has been investigated by using adaptive feedback control strategy. In this model, the

11、 random coupling factor is a random disturbance in the form of Brown motion. Based on Lyapunov stability theorem, It differential equation and LaSalle invariable differential equation theory, the sufficient condition for