6-PSS并联机器人操作机平动工作空间解析

提出一种求解6-PSS并联机器人操作机平动工作空 间 边界的解析方法．该方法将平动工作空间问题归结为三类子空间边界求交问题,即分别由六 张球面片交集构成的上、下边界与由六张椭圆柱面交集构成的侧面边界的求交问题．文中还 提出主工作空间的概念和相应的解析表达及工作空间评价指标,并探讨了设计参数对评价指 标的影响规律．     

高速公路交通的神经控制器

本文分析了高速公路车辆群交通模型并建立了高速公路交通的神经网络模型,提出 了具有入口匝道放行和路段速度两项控制作用的高速公路神经内模控制器,该控制器是一个 状态和控制作用均可跟踪的伺服系统．文章以沈大高速公路为实际背景进行系统仿真实验, 效果良好．     

Inverse filtering and deconvolution

This paper studies the so‐called inverse filtering and deconvolution problem from different angles. To start with, both exact and almost deconvolution problems are formulated, and the necessary and sufficient conditions for their solvability are investigated. Exact and almost deconvolution problems seek filters that can estimate the unknown inputs of the given plant or system either exactly or almostly whatever may be the unintended or disturbance inputs such as measurement noise, external disturbances, and model uncertainties that act on the system. As such they require strong solvability conditions. To alleviate this, several optimal and suboptimal deconvolution problems are formulated and studied. These problems seek filters that can estimate the unknown inputs of the given system either exactly, almostly or optimally in the absence of unintended (disturbance) inputs, and on the other hand, in the presence of unintended (disturbance) inputs, they seek that the influence of such disturbances on the estimation error be as small as possible in a certain norm (H₂ or H_∞) sense. Both continuous‐ and discrete‐time systems are considered. For discrete‐time systems, the counter parts of all the above problems when an ??‐step delay in estimation is present are introduced and studied. Next, we focus on the exact and almost deconvolution but this time when the uncertainties in plant dynamics can be structurally modeled by a Δ‐block as a feedback element to the nominally known plant dynamics. This is done either in the presence or absence of external disturbances. Copyright © 2001 John Wiley & Sons, Ltd.     

Relations Between Regularization and Diffusion Filtering

Regularization may be regarded as diffusion filtering with an implicit time discretization where one single step is used. Thus, iterated regularization with small regularization parameters approximates a diffusion process. The goal of this paper is to analyse relations between noniterated and iterated regularization and diffusion filtering in image processing. In the linear regularization framework, we show that with iterated Tikhonov regularization noise can be better handled than with noniterated. In the nonlinear framework, two filtering strategies are considered: the total variation regularization technique and the diffusion filter technique of Perona and Malik. It is shown that the Perona-Malik equation decreases the total variation during its evolution. While noniterated and iterated total variation regularization is well-posed, one cannot expect to find a minimizing sequence which converges to a minimizer of the corresponding energy functional for the Perona–Malik filter. To overcome this shortcoming, a novel regularization technique of the Perona–Malik process is presented that allows to construct a weakly lower semi-continuous energy functional. In analogy to recently derived results for a well-posed class of regularized Perona–Malik filters, we introduce Lyapunov functionals and convergence results for regularization methods. Experiments on real-world images illustrate that iterated linear regularization performs better than noniterated, while no significant differences between noniterated and iterated total variation regularization have been observed.     

Robot arm reaching through neural inversions and reinforcement learning

We present a neural method that computes the inverse kinematics of any kind of robot manipulators, both redundant and non-redundant. Inverse kinematics solutions are obtained through the inversion of a neural network that has been previously trained to approximate the manipulator forward kinematics. The inversion provides difference vectors in the joint space from difference vectors in the workspace. Our differential inverse kinematics (DIV) approach can be viewed as a neural network implementation of the Jacobian transpose method for arm kinematic control that does not require previous knowledge of the arm forward kinematics. Redundancy can be exploited to obtain a special inverse kinematic solution that meets a particular constraint (e.g. joint limit avoidance) by inverting an additional neural network The usefulness of our DIV approach is further illustrated with sensor-based multilink manipulators that learn collision-free reaching motions in unknown environments. For this task, the neural controller has two modules: a reinforcement-based action generator (AG) and a DIV module that computes goal vectors in the joint space. The actions given by the AG are interpreted with regard to those goal vectors.     

Kinematic Design of Modular Reconfigurable In-Parallel Robots

This paper describes the kinematic design issues of a modular reconfigurable parallel robot. Two types of robot modules, the fixed-dimension joint modules and the variable dimension link modules that can be custom-designed rapidly, are used to facilitate the complex design effort. Module selection and robot configuration enumeration are discussed. The kinematic analysis of modular parallel robots is based on a local frame representation of the Product-Of-Exponentials (POE) formula. Forward displacement analysis algorithms and a workspace visualization scheme are presented for a class of three-legged modular parallel robots. Two three-legged reconfigurable parallel robot configurations are actually built according to the proposed design procedure.     

一类指数型变量均值的Bayes 递进修正估计

基于统计决策理论,给出一种借助先验分布求解一类只有不完全样本的指数型变量均值的Bayes递进修正估计方法,并证明了该方法是最佳的。这是一种动态离散数据融合方法,能够根据观测样本的不断增加而修正估计结果。该方法在预估服役中的导弹武器性能方面具有重要的实用价值。     

A FORMULA FOR THE INVERSE AUTOCORRELATION FUNCTION OF AN AUTOREGRESSIVE PROCESS

Abstract. The determination of the inverse autocorrelation function of a weakly stationary autoregressive process using the autocorrelation function is considered. Usually this is carried out either by using frequency domain methods or by solving first the parameters of the process and then using them. In this paper we give a simple formula by which the inverse autocorrelation function can be determined directly from the autocorrelation function.     

4-3型六自由度并联机构的位置正逆解分析

在对4-3型六自由度进行机构拓扑结构分析得出其耦合度为0的基础上;首先,通过顺序求解该机构各个基本运动链的位置,以求出输出平台的位置正向解析解表达式,再通过求解机构的位置反解,验证了全部正解的准确性.这种基于拓扑结构耦合度分析的位置求解方法,无须通过复杂的数学方法来建立、求解机构位置方程的一元代数高次方程,计算简易,而导出的正逆解析解便于实时控制及其后续的工作空间、误差分析等研究.     

充填采煤液压支架受力分析与运动学仿真研究

根据充填采煤液压支架结构原理及控顶作用,建立了支架顶梁的力学模型,分析得出了顶梁受力情况及3排立柱受力之间的关系;运用Pro/E软件对支架进行三维建模和运动学仿真分析,模拟出主要部件的运动过程,得出各主要部件在工作过程中的运动特征曲线,并对支架参数进行了校核.基于以上分析结果设计制造了ZZC8800/20/38型充填采煤液压支架,支架前、后排立柱受力分别是中立柱支架受力的4.1倍、4.6倍.该支架在平煤十二矿成功应用表明受力分析及设计是科学合理的.