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Qingjie Zhang,Yifeng Niu,Lin Wang,Lincheng Shen,Huayong Zhu 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.6
The average consensus problem of high-order multi-agent systems with multiple time-varying communication delays is investigated in this paper. By using the idea of state decomposition, the condition for guaranteeing average consensus is converted into verifying the stability of zero equi-librium of disagreement system. Considering multiple time-varying communication delays, Lyapunov-Krasovskii approach in time-domain is employed to analyze the stability of zero equilibrium. With the help of Free-weighting Matrices (FWM) approach, the tolerant upper bounds on communication delays can be obtained through solving feasible linear matrix inequalities (LMIs). Delay-dependent stability criteria for both strongly-connected fixed and switching topologies are provided in the main results. Further, the conclusion is extended to the case of jointly-connected switching topologies. Numerical examples and simulation results are given to demonstrate the effectiveness and the benefit on reducing conservativeness of the proposed method.
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Blind Color Image Fusion Based on the Optimal Multi-objective Particle Swarm Optimization
Lincheng Shen,Yifeng Niu 보안공학연구지원센터 2007 International Journal of Multimedia and Ubiquitous Vol.2 No.2
The particle swarm optimization (PSO) is a new swarm intelligence technique inspired by social behavior of bird flocking. In this paper, the optimal multi-objective particle swarm optimization (OMOPSO) is presented. Since the parameters determine the optimization performance of the algorithm, the uniform design is introduced to obtain the optimal combination of the parameters. Additionally, a new crowding operator is used to improve the distribution of nondominated solutions, and ε-dominance is used to fix the size of the set of final solutions. OMOPSO is applied to optimize the parameters of blind color image fusion. First the model of blind color image fusion in YUV color space is established, and then the proper evaluation metrics without the reference image are given, in which a new metrics of conditional mutual information is proposed. Experimental results indicate that the method of blind color image fusion based on OMOPSO realizes the Pareto optimal blind color image fusion.
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