U.S.-Mexico Collaborative Research: Intelligent Control in Manufacturing Via a Fuzzy Logic Based Approach

这个美洲计划奖将支持教授。 John Yen和Reza Langari教授（德克萨斯A M） 工程实验站合作 与Rogelio Soto教授和Jose M. Sanchez，both of the Instituto Tecnologico de 蒙特雷（ITESM）。 建议的研究重点 模糊逻辑的发展 应用的智能控制策略 在制造自动化方面， 制定控制战略， 单元制造的自主运作 流程. 重点将放在应用上 单位的复杂性 制造过程中，和量 所涉及的子系统之间的相互作用， 排除了常规控制的应用 工程方法 操作人员活动的整合 与机组运行有关 制造过程需要能够 控制相当复杂的大规模系统 系统通常是非线性的，从动态的 子系统的观点，并由 多个相互作用的子系统 电流 控制理论中的技术，主要集中在 在线性系统上，不是最佳设计的， 这类问题。 研究人员的目标 为了证明模糊逻辑， 经典逻辑，提供了一种可行的方法， 处理制造过程的现实 控制，因为它使一个人能够处理更多 有效地解决了复杂性问题， 在这种背景下必然会出现。 这 合作应该很好地结合在一起- 在两国建立了研究团队， 解决复杂的管控问题 制造系统。

This Americas Program award will support Prof. John Yen and Prof. Reza Langari of Texas A&M Engineering Experiment Station in collaboration with Prof. Rogelio Soto and Prof. Jose M. Sanchez, both of the Instituto Tecnologico de Monterrey (ITESM). The proposed research focuses on the development of fuzzy logic based intelligent control strategies for applications in manufacturing automation and specifically in the development of control strategies for autonomous operation of unit manufacturing processes. The emphasis will be on application areas where the complexity of the unit manufacturing process, and the amount of interaction among the subsystems involved, preclude the application of conventional control engineering methods. Integration of the activities of human operators in relation to the operation of unit manufacturing processes requires the ability to control rather complex large scale systems These systems are generally nonlinear, from a dynamical subsystems standpoint, and are made up of multiple interacting subsystems. Current techniques in control theory, primarily focused on linear systems, are not optimally designed for this category of problems. The researchers aim to show that fuzzy logic, an alternative to classical logic, provides a viable means for dealing with the reality of manufacturing process control in that it enables one to deal more effectively with the issue of complexity that inevitably arises in this context. This collaboration should bring together well- established research teams in both countries to solve management and control problems of complex manufacturing systems.