双伸位堆垛机系统调度的优化设计

以某机务段段修配件自动化立体仓库(AS/RS)为例,通过分析影响双伸位堆垛机系统运作的重要因素,提出一种基于作业时间最短的优化设计,建立相应的数学模型,并采用分区平均搜索初始种群的遗传算法对其进行验证。结果证明该优化设计有利于提高双伸位堆垛机AS/RS系统的运作效率。     

旋转式倒立摆系统的算法研究及仿真

倒立摆主要有直线式倒立摆、旋转式倒立摆、平面倒立摆等。选取旋转式倒立摆作为研究对象,介绍了系统的机械结构部分,通过分析力学中的拉格朗日法建立了系统的数学模型,研究了两种现代控制算法在旋转式倒立摆系统中的应用：极点配置法及LQR法,并运用MATLAB和SIMULINk工具在两种方法下进行了仿真实验,仿真结果表明：这两种算法在旋转式倒立摆系统的控制中都是可行的,而且效果令人满意。     

移动可伸缩三维倒立摆模型的双足机器人步态控制策略

双足机器人的步态控制策略是保证双足稳定行走的重要条件之一.结合人在行走时ZMP平稳移动的特性,建立了一种移动可伸缩三维倒立摆模型;在约束平面内分析ZMP与COG的运动关系,将ZMP和COG分别定为快变因子和慢变因子,提出了移动可伸缩三维倒立摆模型的双足机器人步态控制策略;最后通过Matlab/ADAMS进行了步态控制仿真研究.仿真结果表明双足机器人可以稳定地行走,验证了该步态控制策略的可行性.     

An effective 3-in-1 keyword search method over heterogeneous data sources

Conventional keyword search engines are restricted to a given data model and cannot easily adapt to unstructured, semi-structured or structured data. In this paper, we propose an efficient and adaptive keyword search method, called EASE, for indexing and querying large collections of heterogeneous data. To achieve high efficiency in processing keyword queries, we first model unstructured, semi-structured and structured data as graphs, and then summarize the graphs and construct graph indices instead of using traditional inverted indices. We propose an extended inverted index to facilitate keyword-based search, and present a novel ranking mechanism for enhancing search effectiveness. We have conducted an extensive experimental study using real datasets, and the results show that EASE achieves both high search efficiency and high accuracy, and outperforms the existing approaches significantly.     

Design of optimized fuzzy cascade controllers by means of Hierarchical Fair Competition-based Genetic Algorithms

In this study, we present a design of an optimized fuzzy cascade controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for a rotary inverted pendulum system. In this system, one controls the movement of a pendulum through the adjustment of a rotating arm. The objective is to control the position of the rotating arm and to make the pendulum maintain the unstable equilibrium point at vertical position. To control the system, we design a fuzzy cascade controller scheme which consists of two fuzzy controllers arrange in a cascaded topology. The parameters of the controller are optimized by means of the HFCGA algorithm. The fuzzy cascade scheme comprises two controllers located in two loops. An inner loop controller governs the position of the rotating arm while an outer controller modifies a set point of the inner controller implied by the changes of the angle of pendulum. The HFCGA being a computationally effective scheme of the Parallel Genetic Algorithm (PGA) has been developed to eliminate an effect of premature convergence encountered in Serial Genetic Algorithms (SGA). It has emerged as an effective optimization vehicle to deal with very large search spaces. A comparative analysis involving computing simulations and practical experiment demonstrates that the proposed HFCGA based fuzzy cascade controller comes with superb performance in comparison with the conventional Linear Quadratic Regulator (LQR) controller as well as HFCGA-based PD cascade controller.     

单级倒立摆的LQR控制和DMC控制Matlab仿真比较

建立了单级直线倒立摆的状态空间模型,分别从线性最优二次型（LQR）控制和模型预测控制的原理出发,在MAT-LAB/SIMULINK环境下,设计了LQR控制器和动态矩阵控制（DMC）控制器,对所建立的倒立摆模型对象进行系统控制仿真。仿真结果表明,作为先进控制的DMC控制的效果比作为最优控制的LQR控制效果更好,鲁棒性更强。     

单级倒立摆的逼近逆模型及趋近控制

基于非线性分级控制思想,研究了逼近逆模型的设计方法,并结合变结构趋近控制律规则,将基于综合误差方法的滑动模逼近控制应用在某单级倒立摆上,通过仿真分析,收到了良好的控制效果.     

基于多重倒排文件的快速相似性检索

提出一种新的高维空间中点数据的索引方法（即MIF）,其基本原理是利用多维倒排文件。和传统索引方法相比,新方法有许多优点,例如它能以较低的复杂度建立索引结构、支持非常高的维数、极低的I／O代价等。实验结果表明,该方法优于传统的索引方法。     

免疫优化神经网络对倒立摆的控制

人工免疫算法是基于生物免疫系统机理和特点发展而来的一种新型智能算法。针对BP神经网络传统训练算法的学习效率低、收敛速度慢且容易陷入局部最优等不足,采用免疫算法对BP神经网络权值进行优化,以实现对倒立摆的控制。实验结果表明,用免疫算法训练神经网络收敛速度快,并能有效避免陷入局部最优。优化后的神经网络能对实际的倒立摆装置进行控制,并取得了满意的效果。     

一类非线性系统的分步变换伪线性化方法

给出了单输入非线性系统的分步变换伪线性化方法及其算法。首先将原系统变换为标准型。利用（1）中的算法,可以获得将标准型变换为伪标准型的变换阵T。在第一步变换下,原系统的部分状态已经获得精确线性化,并且分步变换算法比由原系统直接伪线性化的算法简单,单杆倒立摆的计算机仿真表明了该算法的有效性。