基于支持向量机的计算资源反馈调度

在实时控制系统(RTCS)中,计算资源一般受限。由于诸多不确定性因素和工作负载的动态变化,系统总是运行在不可预期的开放环境中。为保证系统的稳定运行,提出了一种基于支持向量机(SVM)的计算资源反馈调度方法。它周期性地监测系统计算资源,通过SVM在线预测,得到各个控制回路的下一个采样周期,从而实现系统计算资源的动态分配。通过仿真实验验证了该反馈调度方法的性能,并与理想情况、传统开环调度方法进行了比较,显示了其优越性。     

一种改进的基于时空混沌系统的Hash函数构造方法

首先介绍了一种以时空混沌为基础的构造Hash函数的典型方案,并分析了它的不足和安全性问题.在此基础上提出了一种改进的Hash函数构造方法.理论和仿真实验分析表明,该算法具有更好的统计特性和更高的效率,有效地弥补了原算法中存在的碰撞漏洞.     

移动计算环境中易变数据的在线广播调度

随着无线传感器网络、GPS等技术的广泛应用,产生了易变数据这种区别于传统静态数据的新型数据类型,对数据处理方法提出了新的要求.在移动计算环境中,数据广播是一种有效的数据访问方式.针对易变数据的特点提出数据平均不确定率的概念并在此基础上提出一种易变数据在线广播调度策略CEDB-M.仿真实验表明该策略在无传输差错发生、有传输差错发生和多信道广播条件下在获得较优的访问延迟的同时有效降低通过广播读取易变数据的不确定性,有利于基于这些数据的查询结果质量的提高.     

基于加权最小二乘的卡尔曼滤波算法

为了将卡尔曼滤波(KF)应用于非线性系统中,利用了离散采样点将非线性模型线性化.通过加权最小二乘原理.得到近似的线性化模型,再将KF算法应用于这个线性模型中.结果表明,加权最小二乘与KF结合的方法在非线性模型中的计算结果同扩展卡尔曼滤波(EKF)算法接近,且不需要EKF那样求偏导就能很容易地应用到非线性系统中.这种方法实现容易,预测可靠,具有实际应用的价值.     

A piecewise analysis method to stability analysis of linear continuous/discrete systems with time‐varying delay

The delay‐dependent stability problem of linear continuous/discrete systems with time‐varying delay is investigated based on a piecewise analysis method (PAM). In the method, the variation interval of the time delay is firstly divided into several subintervals. By checking the variation of the Lyapunov functional in every subinterval, some new delay‐dependent stability criteria are derived. Several numerical examples show that our method can lead to much less conservative results than those in the existing references. Moreover, when the number of the divided subintervals increases, the corresponding criteria can provide an improvement on the results. Copyright © 2008 John Wiley & Sons, Ltd.     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

Output feedback variable structure control of uncertain linear systems in the presence of actuator dynamics

A new output feedback variable structure control scheme is developed based on a novel passivity idea. This scheme may practically stabilize a class of higher‐relative‐degree uncertain linear systems, and realize output tracking and disturbance attenuation as well. The controller is composed of linear filters and a single relay, without employing real‐time exact differentiators. Under this framework, we also explain how actuator dynamics affect the closed loop behavior. A simulation example shows the simplicity and efficiency of this method. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Exponential stability for uncertain neutral systems with Markov jumps

This paper deals with the global exponential stability problems for stochastic neutral Markov jump systems （MJSs） with uncertain parameters and multiple time-delays. The delays are respectively considered as constant and time varying cases, and the uncertainties are assumed to be norm bounded. By selecting appropriate Lyapunov-Krasovskii functions, it gives the sufficient condition such that the uncertain neutral MJSs are globally exponentially stochastically stable for all admissible uncertainties. The stability criteria are formulated in the form of linear matrix inequalities （LMIs）, which can be easily checked in practice. Finally, two numerical examples are exploited to illustrate the effectiveness of the developed techniques.