The Fuzzy Point Syntheses of Mechanisms

机制的模糊点综合

• 批准号: 9202140
• 负责人: Steven Kramer
• 金额: $ 10.5万
• 依托单位: University of Toledo
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-15 至 1995-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9202140&HistoricalAwards=false
• 关键词: Fuzzy; Point; Syntheses; Mechanisms

This research project involves the integration of fuzzy set theory with the selective precision synthesis method of optimum mechanism design. This effort will enable mechanism designers to effectively solve problems that are posed with fuzzy information. Problems dealing with planar and spatial mechanisms with specified fuzzy motion information will be investigated in this project. Problems will be formulated as nonlinear optimization problems which will be solved using a modified form of the generalized reduced gradient method of optimization. The modification to this optimization method involves its ability to handle fuzzy numbers. This work is important because it will advance the knowledge base in optimum mechanism design in the presence of imprecise data and may open the door for additional engineering applications for the fuzzy set theory.

该研究项目涉及模糊集理论与最优机构设计的选择性精度综合方法的集成。 这项工作将使机制设计者能够有效地解决模糊信息带来的问题。 该项目将研究处理具有指定模糊运动信息的平面和空间机构的问题。 问题将被表述为非线性优化问题，该问题将使用广义降低梯度优化方法的修改形式来解决。 对这种优化方法的修改涉及其处理模糊数的能力。 这项工作很重要，因为它将在存在不精确数据的情况下推进最优机构设计的知识库，并可能为模糊集理论的其他工程应用打开大门。