Liao Xiao-feng

Consensus problems of first-order dynamic multi-agent systems with multiple time delays

Consensus problems of first-order multi-agent systems with multiple time delays are investigated in this paper. We discuss three cases: 1) continuous, 2) discrete, and 3) a continuous system with a proportional plus derivative controller. In each case, the system contains simultaneous communication and input time delays. Supposing a dynamic multi-agent system with directed topology that contains a globally reachable node, the sufficient convergence condition of the system is discussed with respect to each of the three cases based on the generalized Nyquist criterion and the frequency-domain analysis approach, yielding conclusions that are either less conservative than or agree with previously published results. We know that the convergence condition of the system depends mainly on each agents input time delay and the adjacent weights but is independent of the communication delay between agents, whether the system is continuous or discrete. Finally, simulation examples are given to verify the theoretical analysis.

Impulsive Control for Fractional-Order Chaotic Systems

We propose an impulsive control scheme for fractional-order chaotic systems. Based on the Takagi–Sugeno (T-S) fuzzy model and linear matrix inequalities (LMIs), some sufficient conditions are given to stabilize the fractional-order chaotic system via impulsive control. Numerical simulation shows the effectiveness of this approach.

Learning vector quantization neural network method for network intrusion detection

A new intrusion detection method based on learning vector quantization (LVQ) with low overhead and high efficiency is presented. The computer vision system employs LVQ neural networks as classifier to recognize intrusion. The recognition process includes three stages: 1 feature selection and data normalization processing; 2 learning the training data selected from the feature data set; 3 identifying the intrusion and generating the result report of machine condition classification. Experimental results show that the proposed method is promising in terms of detection accuracy, computational expense and implementation for intrusion detection.

Impulsive control for synchronization of nonlinear Rossler chaotic systems

This paper reports that an impulsive control theory for synchronization of nonlinear Rossler chaotic systems is developed. A new framework for impulsive synchronization between such chaotic systems is presented, which makes the synchronization error system a linear impulsive control system. Therefore, it is easy to derive the impulsive synchronization law. The proposed impulsive control scheme is illustrated by nonlinear Rossler chaotic systems and the simulation results demonstrate the effectiveness of the method.

On Impulsive Control for Synchronization and Its Application to Matsumoto-Chua-Kobayashi （MCK） Circuit

The issue of impulsive control theory for synchronization of the MCK circuit is developed. We propose an impulsive control scheme for the complete synchronization of the MCK circuit including chaotic systems. A sufficient condition for the impulsive control is derived, with an easily calculated maximum impulsive interval. The proposed impulsive control scheme is applied to the MCK circuit and the simulation result demonstrates the effectiveness of the method.

An optimized vertical handoff algorithm based on Markov process in vehicle heterogeneous network

In order to solve the problem the existing vertical handoff algorithms of vehicle heterogeneous wireless network do not consider the diversification of networks status, an optimized vertical handoff algorithm based on markov process is proposed and discussed in this paper. This algorithm takes into account that the status transformation of available network will affect the quality of service (QoS) of vehicle terminals communication service. Firstly, Markov process is used to predict the transformation of wireless networks status after the decision via transition probability. Then the weights of evaluating parameters will be determined by fuzzy logic method. Finally, by comparing the total incomes of each wireless network, including handoff decision incomes, handoff execution incomes and communication service incomes after handoff, the optimal network to handoff will be selected. Simulation results show that: the algorithm proposed, compared to the existing algorithm, is able to receive a higher level of load balancing and effectively improves the average blocking rate, packet loss rate and ping-pang effect.

Multidimensional Z-Matrix with Control Parameters and Its Applications in Image Encryption

An n-dimensional Z-matrix with control parameters is presented, and its periodicity and chaos are testified. Experimental results show that the proposed Z-matrix has a long period and changeable periodicity with different dimensions. Some examples of image encryption with a Z-matrix of different dimensions are listed for demonstrating its applications.

Impulsive control of nonlinear systems with time-varying delays

A whole impulsive control scheme of nonlinear systems with time-varying delays, which is an extension for impulsive control of nonlinear systems without time delay, is presented in this paper. Utilizing the Lyapunov functions and the impulsive-type comparison principles, we establish a series of different conditions under which impulsively controlled nonlinear systems with time-varying delays are asymptotically stable. Then we estimate upper bounds of impulse interval and time-varying delays for asymptotically stable control. Finally a numerical example is given to illustrate the effectiveness of the method.

Stability analysis of bidirectional associative memory with axonal signal transmission delays

In this paper, conditions for the existence of equilibrium points and global stability are emphatically discussed for Bidirectional Associative Memory(BAM) models with axonal signal transmission delays, and the discussed methods are more general. The correctness of obtained conclusions is verified by use of some examples. The obtained results have primary significance in the design and application of BAM.

Pinning consensus analysis of multi-agent networks with arbitrary topology

In this paper the pinning consensus of multi-agent networks with arbitrary topology is investigated. Based on the properties of M-matrix, some criteria of pinning consensus are established for the continuous multi-agent network and the results show that the pinning consensus of the dynamical system depends on the smallest real part of the eigenvalue of the matrix which is composed of the Laplacian matrix of the multi-agent network and the pinning control gains. Meanwhile, the relevant work for the discrete-time system is studied and the corresponding criterion is also obtained. Particularly, the fundamental problem of pinning consensus, that is, what kind of node should be pinned, is investigated and the positive answers to this question are presented. Finally, the correctness of our theoretical findings is demonstrated by some numerical simulated examples.