混合变时滞不确定中立型系统鲁棒稳定性分析

研究一类含混合变时滞不确定中立系统时滞相关鲁棒稳定性问题。基于时滞中点值,把时滞区间均分成两部分,通过构造包含时滞中点信息的增广泛函和三重积分项的Lyapunov-Krasovskii (L-K)泛函,利用L-K稳定性定理、积分不等式方法和自由权矩阵技术,建立了一种基于线性矩阵不等式(LMI)的、与离散时滞和中立时滞均相关的鲁棒稳定性判据。数值算例表明,该判据改善了已有文献的结论,具有更低的保守性。     

Development of soft sensor by incorporating the delayed infrequent and irregular measurements

Originated from challenging industrial applications, this paper addresses a soft sensor development problem for linear systems with two types of measurements. One is fast, regular and delay-free measurements. The other is infrequent, irregular measurements with time-varying delays. The approach to be taken is based on the Kalman filter and data fusion technique, avoiding running the full augmented state Kalman filter, and leading to a considerably lower implementation cost. Although it is suboptimal, the loss in performance is minor compared to the optimal filter. Two simulation examples demonstrate the advantages of the proposed approach. An industrial soft sensor application example is also used to demonstrate its practicality.     

基于图像空间的三维动态场景远程可视化方法

对复杂三维动态场景进行远程可视化,基于顶点运动轨迹的压缩、传输方法需要计算的顶点数量巨大,速度慢.针对这些问题,提出一种基于图像空间的三维动态场景远程可视化方法:首先在服务器端进行先空间后时间的自适应采样,获得多幅动画深度图像.通过使用动画深度图像的采样点代替原始动态场景中的顶点,极大减少需要参与计算的三维点数量;然后在每幅动画深度图像中并行压缩采样点的运动轨迹,有效减少压缩时间;最后将压缩后的动态数据传输到客户端并重构一定时间内的三维动态场景.实验结果表明,算法可以极大提高服务器端数据压缩速度,减少需要传输的数据量,有效降低网络带宽对数据传输的限制.     

无线移动网络节点发包概率的演化博弈模型

针对大规模无线移动网络中节点对信道资源的群体性随机博弈问题,在载波侦听多路访问/冲突避免(CSMA/CA)的机制下,建立一种节点发包概率的演化博弈模型。考虑节点成功发送数据包的收益、监听、退避和冲突等成本因素,给出并证明该模型的演化稳定策略(ESS),推导节点发包概率演化的复制动态方程。数值仿真结果表明,该模型能提供更强的ESS,保证在多个移动节点干扰时演化稳定点的鲁棒性。     

Theoretical analysis of a multiple-effect diffusion still producing highly concentrated seawater

A multiple-effect diffusion still producing highly concentrated seawater was theoretically analyzed taking variations of the boiling point elevation (BPE) into account. The still consists of a series of seawater-soaked wicks stuck on closely-spaced parallel plates with the first plate steam-heated at 100°C and the last plate cooled in 30°C ambient air. Evaporation from the wicks increases the BPE more rapidly at downstream distances closer to exits of evaporating areas, and this increase reduces evaporation flux significantly at downstream regions on the wicks. An 80% heat recovery from products of hot condensate and concentrate reduces the steam consumption by 46%. The steam consumption decreases more rapidly with an increasing number of wicks than does the production rate; thus, a lower steam consumption ratio is observed for the still having more wicks. Narrowing the gaps between the plates greatly increases the production rate with a slight decrease in the steam consumption ratio. The still with 19 wicks with 1 m by 2 m evaporating areas, 5 mm gaps and 80% heat recovery produces 12 kg distillate and 3.3 kg concentrate of 0.16 kg/kg-water concentration per 1 kg steam consumption with a 26.4 kg/h distillate production rate.     

基于细胞自动机的动态云实时模拟

具有真实感云的实时模拟应用非常广泛。基于细胞自动机技术建立云模型,明确了边界网格点的处理方法。通过改进变换规则,引入了上升气流的作用,加快了运行速度并反映了云的真实特性。在光照计算过程中,将多重前向散射光照运用于细胞自动机方法中,并将近似米氏散射的Henyey-Greenstein相位函数嵌入到前向散射光照模型。仿真实验表明,该方法提高了云的外观的真实性,可以实现云的实时绘制。     

SSI:一种IPv6/IPv4多址同源识别模型

IPv6/IPv4共存环境下多址同源识别是共存网络管理与拓扑发现的一个关键问题。现有研究主要集中于子网内部的双栈发现及单一IP协议栈中的别名解析,难以识别远程IPv6/IPv4共存网络中的多址同源。通过分析同源地址间的本质联系,提出一种IPv6/IPv4多址同源识别模型(SSI),该模型综合利用特殊地址格式匹配、TCP时钟指纹比对和上层协议短时致瘫等多种方式来提高同源地址的识别能力。实验结果表明,上述方法均可有效识别IPv6/IPv4多址同源;SSI模型具有较理想的识别率和正确率。     

一类混合延迟混沌神经网络的同步

时滞混沌神经网络系统是解空间为无穷维系统,可生成多个正向Lyapunov指数,产生具有高度随机性和不可预测性的混沌甚至超混沌序列,这种特性使得时滞混沌神经网络系统特别适用于保密通信中,混沌同步是保密通信中的关键技术。基于Lyapunov稳定性理论和线性矩阵不等式(LMI)方法,研究了一类具有时变延迟和分布式延迟的混沌神经网络系统的同步问题,考虑系统的内部参数不确定性和外部干扰及混合时滞等因素,将系统时滞项加入所设计的控制器中,给出了保证误差系统的全局均方渐近稳定的充分条件和控制律,实现驱动系统和响应系统的同步。与其它方法相比,所设计的含有时滞项的控制器提高了系统误差精度及反应速率。最后,通过仿真实例,验证了所提方法的有效性。     

一类多时变时滞T-S模糊广义系统的容许控制

研究了一类具有多时变时滞的T-S模糊广义系统的容许控制问题。首先,给出了多时变时滞的T-S模糊广义系统数学模型,并且利用Lyapunov稳定性分析方法,得到了多时变时滞的T-S模糊广义系统的容许的一个充分条件,所得的结果对时变时滞的变化率没有限制。该充分条件可以通过严格线性矩阵不等式来求解。然后基于所给出的容许性定理,提出了状态反馈控制器的设计方法.最后,使用算例说明了所给方法的可行性和有效性。     

Introducing robustness in model predictive control with multiple modelsand switching

Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.