基于灰关联混合蛙跳算法的雷达波形设计

提出了一种基于灰关联混合蛙跳算法的雷达波形设计方法,以混合蛙跳算法为主体,在局部更 新算子中引入遗传算法的遗传算子,并改进原始蛙跳算法的分组方法,丰富了种群的多样性,同时引入灰关联综合评价法则对适应度函数值加以关联度分析。文中以设计具有低自相关旁瓣和互相关特性的正交多相编码为例,将该算法用于雷达波形设计中。仿真结果表明使用本文算法产生 的波形具备较好的低自相关特性和互相关特性,表明了该算法是有效和可行的。     

Less conservative stability criteria for linear systems with interval time‐varying delays

The problem of the stability of a linear system with an interval time‐varying delay is investigated. A new Lyapunov–Krasovskii functional that fully uses information about the lower bound of the time‐varying delay is constructed to derive new stability criteria. It is proved that the proposed Lyapunov–Krasovskii functional can lead to less conservative results than some existing ones. Based on the proposed Lyapunov–Krasovskii functional, two stability conditions are developed using two different methods to estimate Lyapunov–Krasovskii functional's derivative. Two numerical examples are given to illustrate that the two stability conditions are complementary and yield a larger maximum upper bound of the time‐varying delay than some existing results. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed non-cooperative robust MPC based on reduced-order models

In this paper, a non-cooperative distributed MPC algorithm based on reduced order model is proposed to stabilize large-scale systems. The large-scale system consists of a group of interconnected subsystems. Each subsystem can be partitioned into two parts: measurable part, whose states can be directly measured by sensors, and the unmeasurable part. In the online computation phase, only the measurable dynamics of the corresponding subsystem and neighbour-to-neighbour communication are necessary for the local controller design. Satisfaction of the state constraints and the practical stability are guaranteed while the complexity of the optimization problem is reduced. Numerical examples are given to show the effectiveness of this algorithm.     

Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

噪声系数的测量方法研究

该文介绍了三种测量噪声系数的方法：增益法,Y因子法和冷源法。重点介绍了当我们做精确测量时Y因子法的不足和冷源法的突破以及给出了这两种方法的实际测试例子。     

基于RBAC的用户权限管理的研究与实现

随着计算机网络信息技术的不断发展,用户权限管理已经成为一个日益突出的问题。该文针对基于传统的RBAC模型在权限管理中存在的一些不足,分析了目前用户权限管理结构的设计,并以学校办公自动化管理系统中的用户权限设计为例,给出了一种基于角色的用户权限管理的新权限管理方法的设计与实现,实践证明此方法在办公自动化管理系统的适用性、可操作性及安全性等方面都有很大提高。     

基于WIA-PA安全标准的网络密钥管理机制设计分析

WIA-PA安全标准隶属于过程自动化领域,是由我国工业无线联盟制定的基于IEEE802.15.4标准的无线网络系统,属于WIA的子标准,主要用于工业过程中无线短程网的控制、测量以及监视。基于WIA-PA安全标准网络密钥管理机制设计的内容主要包括基于WIA-PA安全标准的密钥基本管理设计、基于WIA-PA安全标准的入网安全性设计、基于WIA-PA安全标准的数据流安全传输设计、基于WIA-PA安全标准的系统实用性研究设计、基于WIA-PA安全标准的系统性能研究设计。     

Pulse-order recursive method for inverse covariance matrix computation applied to space-time adaptive processing

The conventional space-time adaptive processing(STAP) method such as the typical sample matrix inversion(SMI)-based STAP method is difficult to implement for a practical system because intense computational complexity arises in calculating the inversion of a space-time covariance matrix directly.According to the block Hermitian matrix property of space-time covariance matrix,a new pulse-order recursive method is proposed in this paper to calculate the inverse covariance matrix for the STAP adaptive weight,which can reduce the computational complexity significantly.The proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix property.In the following,the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance matrix.Next,the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously obtained.Compared with the conventional SMI-based STAP algorithms,the computational complexity of the proposed method is reduced to more than 50% for the same clutter suppression performance.This method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.