Intelligent Control Concepts for Computer Numerical Control Machines

计算机数控机床的智能控制概念

• 批准号: 9625814
• 负责人: Albert Bennett
• 金额: $ 10万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-15 至 2002-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9625814&HistoricalAwards=false
• 关键词: Intelligent; Control; Concepts; Computer; Numerical

9625814 Bowden The objective of this research is to design and develop a prototype sensor fusion adaptive critic neurocontrol system which will generate the cut paths for a computer numerical control (CNC) machine given only the desired surface shape and the maximum allowable surface error. This research will lay the foundation for the development of software and hardware simplify the interface between the product design and automated fabrication processes and to improve product quality. It attempts a technological leap in adaptive controls research for CNC machining processes and a major advance in as well. This group will develop, test, and demonstrate a novel sensor fusion adaptive critic neurocontrol system for cutting airfoil shaped ruled surfaces. The neurocontrol system will provide a 5-axis milling machine with the intelligence to cut molds for airfoil shapes based on a mathematical description of the desired shape. The neurocontrol system will make use of the multiple sensor readings available during the cutting process as inputs to the adaptive critic. The sensor information will be fused for dimensionality reduction and to provide greater richness of inputs. The adaptive critic is a powerful method for adaptive control. To maximize the probability of successfully achieving the research objective, a cross-disciplinary team of experts has been assembled for the project. Members of the team come from the Department of Industrial Engineering at Mississippi State University (MSU), MSU's Raspet Flight Research Laboratory (RFRL), and Accurate Automaton Corporation. Mississippi State University's RFRL has a strong precision mold making activity and Accurate Automation Corporation has an extensive history in neural network system development. ***

本研究的目的是设计和开发一个原型传感器融合自适应批评神经控制系统，该系统将仅给定所需的表面形状和最大允许的表面误差，为计算机数控（CNC）机床生成切割路径。本研究将为软件和硬件的发展奠定基础，简化产品设计和自动化制造过程之间的接口，提高产品质量。它是数控加工过程自适应控制研究的技术飞跃，也是自适应控制研究的重大进展。该小组将开发、测试和演示一种用于切割翼型直纹表面的新型传感器融合自适应批评神经控制系统。神经控制系统将提供一个5轴铣床与智能切割模具的翼型形状的基础上所需的形状的数学描述。神经控制系统将利用切割过程中可用的多个传感器读数作为自适应批评家的输入。传感器信息将被融合以降低维数，并提供更丰富的输入。自适应批评是一种有效的自适应控制方法。为了使成功实现研究目标的可能性最大化，已经为该项目组建了一个跨学科的专家小组。该团队的成员来自密西西比州立大学（MSU）工业工程系、MSU的Raspet飞行研究实验室（RFRL）和Accurate Automaton公司。密西西比州立大学的RFRL拥有强大的精密模具制造活动，而精确自动化公司在神经网络系统开发方面有着悠久的历史。＊＊＊