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. ***
