计算机网络互连模式及实现技术

本文讨论了计算机网络互连的体系结构模式及实现技术。文中先论述了ＩＳＯ、ＤＯＤ和Ｐｕｐ网际互连参考模式，然后讨论了网络互连的主要实现技术：互连层，网际寻址，网际路由选择，信包分拆与重装，网际流控与拥挤控制，网际保安与差错控制，网际信关与桥以及协议转换等技术。     

Protein modelling using a chimera reference protein derived from exons

Bovine pancreatic /S-trypsin (PDB ID-code: 1TPO) which is registeredin the Brookhaven Protein Data Bank (PDB) consists of four exons.The results of homology searches for each exon in the PDB showedthat homologous proteins were tonin (PDB ID-code: 1TON), ratmast cell protease (PDB ID-code: 3RP2_A), kaffikrein A (PDBID-code: 2PKA_B) and kallikrein A (2PKA_B) respectively. Thus,for the three-dimensional structure prediction of 1TPO, a chimeraprotein was constructed from the three proteins mentioned aboveand the 3-D structure prediction was performed using this chimerareference protein. The modelled structure of 1TPO was energeticallyoptimized by molecular mechanics and molecular dynamics simulationand was compared with its X-ray crystal structure registeredin the PDB. The root mean square deviations (r.m.s.d.) of mainchain atoms and the neighbouring active site (5 sphere fromHis57, AsplO2 and Serl95) between the modelled structure andthe X-ray structure were 1.66 and 0.94 respectively. Porcinepancreatic elastase (PDB ID-code: 3EST) which is registeredin the PDB was used as the reference protein and the modelledstructure from 3EST was also compared with the X-ray data. Ther.m.s.d. of main chain atoms and that of the active site were2.14 and 1.18 respectively. These results dearly support thepropriety of this method using the chimera reference protein.     

容纳矛盾逻辑系统与悖论

分析了目前各种容纳矛盾逻辑系统的不足,提出了正域、反域、不动域的概念,进而发现悖论是逻辑思维领域的不动点,建立了一个容纳矛盾的逻辑系统S,并给出了系统S的语义模型,证明了系统S的元定理.在系统S中,命题演算被分成3个独立的域,正域、反域中所有经典逻辑的定理与演算模式都是有效的;不动域是一个包含矛盾的域,在不动域中,可以证明悖论是一个定理.系统S与Da Costa的次协调逻辑系统Cn相比较,它不但可以容纳矛盾,并且可以把矛盾解释清晰.以此逻辑系统为基础,可以建立一个容纳矛盾的数学基础.     

带曲率补偿的带隙基准电流源的设计

简单介绍了带隙基准源的基本原理,给出了一款基于Widlar结构的带曲率补偿的带隙基准电压电流源的设计方法,通过采用TSMC₀.5μm工艺库对电路进行仿真,在-40～150℃的温度范围内,其带隙基准的输出具有12ppm/℃的温度系数,电流基准的输出具有42ppm/℃。此外,文中还对曲率补偿电路的工作原理进行了分析,并且通过仿真波形对曲率补偿的工作机制进行了讨论。     

多站虚拟量测变换均值无源定位算法

在多站无源均值定位算法中,为了解决部分传感器间夹角过大或过小所导致的定位精度下降问题,提出一种基于虚拟量测变换的多传感器管理无源定位算法.首先在全局坐标系下分析了传感器间夹角对误差几何稀释度(GDOP)的影响,进而得到双站获得较好定位精度的夹角约束关系;其次针对不满足该约束关系的传感器组合提出一种虚拟量测变换定位算法,通过空间管理的方法达到对传感器的优化布站,并结合算法的实施步骤对其原理及特点进行了理论分析,尤其对变换前后的交点精度进行了比较.仿真结果表明虚拟量测算法的定位精度要明显优于均值算法,进而说明该算法的有效性及传感器管理在多站无源定位中的重要作用.     

新的e修正鲁棒自适应控制方法在航空发动机上的应用

针对航空发动机模型的结构和参数的不确定性,提出一种基于非李亚普诺夫方程(NQLF)的e修正鲁棒模型参考自适应控制法。该方法无需知道发动机精确数学模型,抗干扰能力强,在输出误差信号的作用下具有比普通方法更快的收敛性,振荡性能够得到很好的控制。从仿真结果可见控制器能使系统比较好地跟踪参考模型的输出,对发动机模型参数和结构的变化有一定的适应能力,鲁棒性较好。     

基于内在奖励的技能获取和组合方法

现有的内在奖励随着agent不断探索环境而逐渐消失,导致了agent无法利用内在奖励信号去指引agent寻找最优策略。为了解决这个问题,提出了一种基于内在奖励的技能获取和组合方法。该方法首先在agent与环境交互过程中寻找积极状态,在积极状态中筛选子目标;其次从初始状态到达子目标,子目标到达终止状态所产生的一条轨迹中发现技能,对技能中出现一个或者两个以上的子目标进行组合;最后用初始状态到子目标的距离和初始状态到子目标的累积奖励值对技能进行评估。该方法在Mujoco环境中取得了较高的平均奖励值,尤其是在外在奖励延迟的情况下,也能取得较好的平均奖励值。说明该方法提出的子目标和技能可以有效地解决内在奖励消失后,agent无法利用内在奖励信号学习最优策略的问题。     

Positive state‐bounding observer for positive interval continuous‐time systems with time delay

This paper is concerned with the problem of positive observer synthesis for positive systems with both interval parameter uncertainties and time delay. Conventional observers may no longer be applicable for such kind of systems due to the positivity constraint on the observers, and they only provide an estimate of the system state in an asymptotic way. A pair of positive observers with state‐bounding feature is proposed to estimate the state of positive systems at all times in this paper. A necessary and sufficient condition for the existence of desired observers is first established, and the observer matrices can be obtained easily through the solutions of a set of linear matrix inequalities (LMIs). Then, to reduce the error signal between the system state and its estimates, an iterative LMI algorithm is developed to compute the optimized state‐bounding observer matrices. Finally, a numerical example is presented to show the effectiveness and applicability of the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

A critical review of the most popular types of neuro control

In this review article, the most popular types of neural network control systems are briefly introduced and their main features are reviewed. Neuro control systems are defined as control systems in which at least one artificial neural network (ANN) is directly involved in generating the control command. Initially, neural networks were mostly used to model system dynamics inversely to produce a control command which pushes the system towards a desired or reference value of the output (1989). At the next stage, neural networks were trained to track a reference model, and ANN model reference control appeared (1990). In that method, ANNs were used to extend the application of adaptive reference model control, which was a well‐known control technique. This attitude towards the extension of the application of well‐known control methods using ANNs was followed by the development of ANN model‐predictive (1991), ANN sliding mode (1994) and ANN feedback linearization (1995) techniques. As the first category of neuro controllers, inverse dynamics ANN controllers were frequently used to form a control system together with other controllers, but this attitude faded as other types of ANN control systems were developed. However, recently, this approach has been revived. In the last decade, control system designers started to use ANNs to compensate/cancel undesired or uncertain parts of systems' dynamics to facilitate the use of well‐known conventional control systems. The resultant control system usually includes two or three controllers. In this paper, applications of different ANN control systems are also addressed. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

FMS的模型参考自适应调度

用运筹学研究生产线调度问题已有几十年的历史,但由此得出的调度策略的实时性很差.1986年自动控制工作者提出了“PMS动态自适应计算机调”一词.令人感到十分新奇.可惜.从未见到任何有关的论文.本文研究FMS的模型参考自适应调度.本文采用我们提出的考虑了有限缓冲器容量的极大代数模型.环境的影响反映于对象参数的摄动,本文采用我们提出的摄动计算方法.调度器的设计采用次梯度法,以求解连续变量和离散变量混合的优化问题,附有数字实例,计算和仿真表明:FMS的模型参考自适应调度是可行的,是值得继续深入研究的。