Optimality-criteria-based probabilistic structural design

The possibility of extending absolute minimum weight designs for sandwich beam systems or fibre-reinforced beams and plates is considered when both the extreme loading applied to the system and the beam bending resistance properties are described in probabilistic rather than deterministic terms. It is shown that such an extension is possible provided certain plausible assumptions are made about the probabilistic modelling of the system. Examples considered include simple and continuous beams under loading of uncertain magnitude, direction or location. It is shown that the classical (deterministic) optimal solutions remain valid under reasonable assumptions. The extension of the probabilistic solutions to a wider class of examples is discussed. Received October 20, 2000     

On the two-degree-of-freedom Wiener–Hopf optimal design with tracking and disturbance rejection constraints

In this paper, the design of the two-degree-of-freedom optimal Wiener–Hopf controller with asymptotic tracking and disturbance rejection constraints is studied. Based on the solvability conditions and the solution parameterization of Diophantine equations over the stable rational fractional ring M(s), the disturbance rejection problem in the general case is solved. A simple cost function is defined to reflect the transient performance of control signal caused by deterministic signals. Finally, the design of the two-degree-of-freedom optimal Wiener–Hopf controller is presented.     

机载脉冲多普勒雷达DBS成像实验研究

脉冲多普勒雷达是现代战斗机普遍采用的一种典型雷达体制。多普勒波束锐化（DBS）已成为机载脉冲多普勒雷达在空／地工作模式中对地面进行高分辨成像的有效途径,因而受到了国内外广泛的重视。本文首先分析了DBS技术的基本原理及其实现步骤,针对载机惯导参数误差较大的实际情况,应用本文提出的新的多普勒质心估计算法－－“曲线拟合相位较正叠代算法”,对某型脉冲多普勒雷达的实测数据进行了成像处理实验研究,给出了实测数据的DBS成像结果,证明了处理过程的有效性。     

Structural Synthesis of Modular Weakly Connected Neural Networks. II. Nuclear Neural Networks

The simplest modular neural network is investigated, in which each module is a single-layer perceptron (a neural kernel). Numerical indices of quality by the criteria of operating speed and plasticity are proposed to characterize structural properties of nuclear neural networks. Based on the indices introduced, optimum procedures of structural synthesis are constructed.     

Stabilization of Dynamic Systems Providing Additional Properties of Transients

The problem is to construct bounded stabilization feedbacks that provide additional properties of transient processes (degree of stability, oscillation, absence of overshoot, monotonicity). The problem is solved by means of optimal control methods. The results are illustrated by an example of stabilization of a dynamic fourth-order system.     

A Deformation Field for Euler–Bernoulli Beams with Applications to Flexible Multibody Dynamics

The deformation field commonly used for Euler–Bernoulli beamsin structural dynamics is investigated to determine its suitability foruse in flexible multibody dynamics. It is found that the traditionaldeformation field fails to produce an elastic rotation matrix that iscomplete to second-order in the deformation variables. A completesecond-order deformation field is proposed along with the equationsneeded to incorporate the beam model into a graph-theoretic formulationfor flexible multibody dynamics [1]. This beam modeland formulation have been implemented in a symbolic computer programcalled DynaFlex that can use Taylor, Chebyshev, or Legendrepolynomials as the basis functions in a Rayleigh–Ritz discretizationof the beam's deformation variables. To demonstrate the effects of the proposed second-order deformationfield on the response of a flexible multibody system,two examples are presented.     

Neural Network Based Algorithm for Dynamic System Optimization

A class of artificial neural networks with a two‐layer feedback topology to solve nonlinear discrete dynamic optimization problems is developed. Generalized recurrent neuron models are introduced. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. A comparative analysis of the computational requirements is made. The analysis shows advantages of this approach as compared to the standard dynamic programming algorithm. The technique has been applied to several important optimization problems, such as shortest path and control optimal problems.     

An Estimation of Complexity and Computational Costs for Vertical Block-Cyclic Distributed Parallel LU Factorization

The Vertical Block–cyclic Distributed Parallel LU Factorization Method (VBPLU) is effectively processed on a distributed memory parallel computer. VBPLU is based on the two techniques, the block algorithm and the aggregation of communications. Since startup time dominates the data communication and the aggregation reduces communication isssues, the total performance has been much improved. Furthermore this method uses long vectors so that it is also advantageous on vector processors. In this paper, we have constructed a modeling of VBPLU using a simplified LogGP model with analytical formulae, and estimated accurately the computational cost taking into account load distributions caused by data layout and process mapping. Some knowledge for optimization of block algorithm has been obtained. Our estimations have been verified through numerical experiments on three different distributed memory parallel computers.     

激光制导武器的发展现状与趋势

本文简要讨论了激光制导的原理及工作方式,对典型激光制导武器进行了详细介绍,通过分析激光制导武器的特点,重点描述了中外各国激光制导武器的发展现状,对激光武器的攻防战略及其发展趋势也作出了一定阐述。     

单级倒立摆建模及其控制方法设计

单级倒立摆控制是一个即复杂而又对准确性、快速性要求很高的非线性不稳定系统控制问题。单级倒立摆数学模型的建立对研究其稳定性具有指导作用。用拉格朗日功能平衡法建立了倒立摆的刚体动力学方程,采用了LQR法对其进行了控制设计,并且进行了MATLAB仿真,结果表明此方法均可以成功控制倒立摆,使其稳定并具有良好的鲁棒性。