Passivity analysis of complex dynamical networks with multiple time-varying delays

Abstract

We investigate input passivity and output passivity for a generalized complex network with non-linear, time-varying, non-symmetric and delayed coupling. By constructing some suitable Lyapunov functionals, several sufficient conditions ensuring input passivity and output passivity are derived for complex dynamical networks. Finally, two numerical examples are given to show the effectiveness of the obtained results.

Exponential Synchronization of Impulsive Complex Networks with Output Coupling

“…In the above, two sufficient conditions are given to ensure the global exponential state synchronization of network (1). Next, we shall investigate the output synchronization of complex network (1).…”

“…[27] The complex network (1) is said to achieve output synchronization if lim t→+∞ yi(t) − yj(t) = 0, for all i, j = 1, 2, · · · , N. Definition 3. (see [1]) Let A = (aij)m×n ∈ R m×n and B = (bij)p×q ∈ R p×q . Then the Kronecker product (or tensor product) of A and B is defined as…”

“…Some well-known examples include food webs, communication networks, social networks, power grids, cellular networks, world wide web, metabolic systems, disease transmission networks, etc. [1,2] In particular, the synchronization problem has received much of the focus in recent years. A wide variety of synchronization criteria have been presented for various complex networks [3−25] .…”

Stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay

“…Passive properties of systems can keep the systems internally stable. Due to its importance, the problem of passivity analysis for delayed dynamic systems has been investigated by many researchers and lots of results have been reported in the literature [20][21][22][23][24][25][26]. For instance, the passivity condition for discrete-time switched neural networks with various functions and mixed time delays was derived [22].…”

Passivity Analysis of Complex Delayed Dynamical Networks with Output Coupling

“…Passivity [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] is an important concept of system theory and provides a nice tool for analyzing the stability of systems and has found applications in diverse areas such as stability, complexity, signal processing, chaos control and synchronization, and fuzzy control. Many researchers have studied the passivity of fuzzy systems [19][20][21][22] and neural networks [23][24][25][26][27][28].…”