OPTIMAL CONTROL ELIMINATING SWING FOR THE LIFTING CAPACITY

This paper discusses the model for lifting capacity of the crane and optimal con-trol of eliminating swing in lifting process. One half loop control method is presented, which is onlyto examine and measure the trolley speed for eleiminating swing.The fact shows this methOd is sim-ple and practicle for enginceering.     

EXISTENCE OF A BASIC OPTIMAL SOLUTION FOR LINEAR VECTOR EXTREME VALUE PROBBEM

In this paper, the concept of basic for linear vector extreme value problem is introduced in the partially ordered vector space. Some properties and results of the linear programming are generalized. And the existaence therom of basic optimal solution is proved.     

饲草压捆机压缩机构有限元分析

为了牧草资源的合理匹配,推动饲草产业化进程,进行了饲草压捆机设计与研制。在设计中将先进的工业设计软件Pro/Engineer和ANSYS有限元分析软件有机结合,对压捆机的关键机构——压缩机构进行了建模和结构分析,优化了结构设计,提高了设计的可行性,增加了农机设计的科技含量。     

面向大规模定制的产品族模糊层次优化研究

基于对目前产品平台设计的研究综述，分析并指出了研究中的不足。介绍了产品平台的概念和特征，探讨了基于公共平台的产品族设计方法。提出了基于主从关联结构的层次优化设计理念，以及实现这一理念的方法和模型框架：并对模型的数学形式、模糊层次优化做了阐述。     

灌溉兼防洪水库的优化调度

我国干旱半干旱地区，天然降水量少且时程及地域相差大，并有很大的随机性。对有水库调节的地区，如何处理天然降水的随机性，合理利用有限的水资源，解决人畜饮水、工业用水、林业及农业灌溉耗水，使其在各种情况下都能达到最佳的社会效益和经济效益，该文选用动态规划法，编制的电算程序，很好地解决了这一问题。     

闸门的优化设计

用平面体系的方法进行结构分析，对排灌机械中平面钢闸门的面板－梁格体系的优化设计进行了探讨，用边界搜索法将有约束优化问题转换为无约束优化问题，给出了优化设计程序框图进行实例理论验证，结果表明，彩本文介绍的优化方法设计，闸门的叶体积可减小２０％左右。     

属性识别模型在水利水电规划方案综合优选中的应用

针对目前水利水电规划方案综合优选方法中存在的问题，提出了基于变异系数权重的水利水电规划方案综合优选属性识别模型。该模型采用反映评价指标特征值之间差异性的参数——变异系数作为评价指标的权重，减小了权重确定的主观性，且模型求解方法简单易学。实例分析表明，这一模型和方法是合理、可行的。     

Sensitivity analysis of optimal operation of irrigation supply systems with water quality considerations

A model for optimal operation of water supply/irrigation systems of various water quality sources, with treatment plants, multiple water quality conservative factors, and dilution junctions is presented. The objective function includes water cost at the sources, water conveyance costs which account for the hydraulics of the network indirectly, water treatment cost, and yield reduction costs of irrigated crops due to irrigation with poor quality water. The model can be used for systems with supply by canals as well as pipes, which serve both drinking water demands of urban/rural consumers and field irrigation requirements. The general nonlinear optimization problem has been simplified by decomposing it to a problem with linear constraints and nonlinear objective function. This problem is solved using the projected gradient method. The method is demonstrated for a regional water supply system in southern Israel that contains 39 pipes, 37 nodes, 11 sources, 10 agricultural consumers, and 4 domestic consumers. The optimal operation solution is described by discharge and salinity values for all pipes of the network. Sensitivity of the optimal solution to changes in the parameters is examined. The solution was found to be sensitive to the upper limit on drinking water quality, with total cost being reduced by 5% as the upper limit increases from 260 to 600 mg Cl l^–1. The effect of income from unit crop yield is more pronounced. An increase of income by a factor of 20 results in an increase of the total cost by a factor of 3, thus encouraging more use of fresh water as long as the marginal cost of water supply is smaller than the marginal decrease in yield loss. The effect of conveyance cost becomes more pronounced as its cost increases. An increase by a factor of 100 results in an increase of the total cost by about 14%. The network studied has a long pipe that connects two distinct parts of the network and permits the supply of fresh water from one part to the other. Increasing the maximum permitted discharge in this pipe from 0 to 200 m³ h^–1 reduces the total cost by 11%. Increasing the maximum discharge at one of the sources from 90 to 300 m³ h^–1 reduces the total cost by about 8%.     

基于NNARMAX模型的地下水位预报研究

区域地下水系统是一个受多种因素影响的复杂的非线性动态系统 ,应用遗忘因子的递归最小二乘( RLS)算法进行训练 ,采用通过减少网络节点间的连接权值 ,进而裁减冗余节点来选择适宜的网络拓扑结构 ,建立了非线性自回归滑动平均神经网络 ( NNARMAX)模型 ,地下水位预报结果表明 :通过对网络结构的优化达到了自动确定非线性自回归模型阶数和影响因素的选择 ,能有效地表示区域地下水动态系统内部及其外部诸多影响因素间的不确定关系 ,是预测区域地下水动态变化较为有效的方法之一。     

基于粒子群优化算法与混合罚函数

粒子群算法(PSO)具有简单易实现，可调参数少的优点。将其用于最优潮流的求解，结合混合罚函数来限制最优潮流的约束条件，使粒子群算法的寻优速度加快，迭代次数减少。通过在IEEE9节点和IEEE30节点上的仿真计算表明，该算法在优迭代速度和收敛精度上都取得了较好的效果。