Stabilizing composite control for a class of linear systems modeled by singularly perturbed Ito differential equations

In this paper, the problem of robust H_∞ control is investigated for sampled-data systems with probabilistic sampling. The parameter uncertainties are time-varying norm-bounded and appear in both the state and input matrices. For the simplicity of technical development, only two different sampling periods are considered whose occurrence probabilities are given constants and satisfy Bernoulli distribution, which can be further extended to the case with multiple stochastic sampling periods. By applying an input delay approach, the probabilistic sampling system is transformed into a continuous time-delay system with stochastic parameters in the system matrices. By linear matrix inequality (LMI) approach, sufficient conditions are obtained, which guarantee the robust mean-square exponential stability of the system with an H_∞ performance. Moreover, an H_∞ controller design procedure is then proposed. An illustrative example is included to demonstrate the effectiveness of the proposed techniques.     

Real-time approximation of molecular interaction interfaces based on hierarchical space decomposition

The interaction interface between two molecules can be represented as a bisector surface equidistant from the two sets of spheres of varying radii representing atoms. We recursively divide a box containing both sphere-sets into uniform pairs of sub-boxes. The distance from each new box to each sphere-set is conservatively approximated by an interval, and the number of sphere-box computations is greatly reduced by pre-partitioning each sphere-set using a kd-tree. The subdivision terminates at a specified resolution, creating a box partition (BP) tree. A piecewise linear approximation of the bisector surface is then obtained by traversing the leaves of the BP tree and connecting points equidistant from the sphere-sets. In 124 experiments with up to 16,728 spheres, a bisector surface with a resolution of 1/2⁴ of the original bounding box was obtained in 28.8 ms on average.     

Group path covering and distance two labeling of graphs

For a positive integer d, an L(d,1)-labeling f of a graph G is an assignment of integers to the vertices of G such that |f(u)−f(v)|?d if uv∈E(G), and |f(u)−f(v)|?1 if u and u are at distance two. The span of an L(d,1)-labeling f of a graph is the absolute difference between the maximum and minimum integers used by f. The L(d,1)-labeling number of G, denoted by λd,1(G), is the minimum span over all L(d,1)-labelings of G. An L^′(d,1)-labeling of a graph G is an L(d,1)-labeling of G which assigns different labels to different vertices. Denote by the L^′(d,1)-labeling number of G. Georges et al. [Discrete Math. 135 (1994) 103-111] established relationship between the L(2,1)-labeling number of a graph G and the path covering number of Gc, the complement of G. In this paper we first generalize the concept of the path covering of a graph to the t-group path covering. Then we establish the relationship between the L^′(d,1)-labeling number of a graph G and the (d−1)-group path covering number of Gc. Using this result, we prove that and for bipartite graphs G can be computed in polynomial time.     

Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.     

基于ATmega16L的PID温控系统设计

详细介绍了基于ATmega16L为核心的温度控制系统设计,传感器用Pt100并以PID算法进行温控,上位机PC与ATmega16L单片机之间通过串口通信。可对工作现场实时监控、温度曲线显示。参数设定后下位机可独立进行相应的PID控制运算控制PWM,来控制调节温度。应用于样品烘制的温度控制,具有成本低精度高、易于维护的特点。     

基于SPI通信的便携式电子膨胀阀控制器设计

研究了一种基于SPI通信的便携式电子膨胀阀控制器设计.该设计采用主控制板和按键显示板两个独立单片机系统的架构,且两个单片机系统之间应用SPI通信进行实时数据交换.详细介绍了SPI通信技术以及Atmega16单片机的SPI通信接口,并给出该便携式电子膨胀阀控制器的SPI通信部分的软件流程图.     

基于ATMEGA16语音录放系统的设计与实现

介绍了具有较强通用性的语音告警系统。系统通过单片机ATMEGA16控制语音芯片ISD1790,实现了在不同情况下提供不同的语音提示告警,且提示语音可以自行录入。最后通过D类音频功率放大器TPA3101D2,实现了高音质大音量语音输出。     

基于Atmega16单片机的重物提升控制系统设计

为了实现对重物提升的精确控制,设计中选择了以Atmegal6单片机为核心的控制系统。根据控制要求,提出了实施以单片机主、从结构的控制方式。重点介绍了用光电编码器作为传感器、对传感器输出的脉冲信号进行整形、鉴相后送入单片机计数的硬件电路和单片机对计数脉冲、设定位移量进行计算处理的软件程序,根据计算结果完成相应的智能化控制。     

教室智能LED照明系统设计

针对学校教室照明的舒适性、节能性以及智能化管理的需求,设计了一种新型教室智能LED照明系统。系统以PC机作为中央控制器,以PIC16F873A作为微控制器,利用RS485作为通信网络,实现整个教学楼教室LED灯的自动开/关灯和PWM调光。     

虚拟企业信息集成系统中企业信息对象的设计与实现

竞争迫使现代企业去寻找新的信息集成技术来管理他们的企业 .为支持虚拟企业环境下的信息集成 ,本文结合企业信息的特点 ,根据信息的不同处理手段对企业信息进行分类 ,划分为不同的企业信息对象 ,并基于 CORBA在一个虚拟企业集成系统 Via Scope中设计、实现了不同企业信息对象的管理