Additive manufacturing (AM) uses computer-aided design to construct parts layer by layer. Relative to traditional manufacturing processes, AM provides a time-efficient and cost-effective way to produce low-volume, customized parts with complex geometries. This work presents an improved Cross-Coupled iterative learning control (CCILC) scheme to overcome current limitations in contour following for complex, free-form curves in AM. The approach involves modifying the definition of the error vector used in the individual axis iterative learning controllers and defining time varying weightings based on the curvature of the reference trajectory to couple tracking and contour errors. In this paper, the design for the improved CCILC system is presented, and the performance of this system is compared to the performance of existing ILC control schemes via simulations. In comparison to the current control methods, the simulation results demonstrate significant performance improvements for contour tracking of a reference trajectory with high levels of curvature.
- Dynamic Systems and Control Division
Improved Cross-Coupled Iterative Learning Control for Contouring NURBS Curves Available to Purchase
Armstrong, A, Johnson, AW, & Alleyne, A. "Improved Cross-Coupled Iterative Learning Control for Contouring NURBS Curves." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems. Atlanta, Georgia, USA. September 30–October 3, 2018. V002T23A005. ASME. https://doi.org/10.1115/DSCC2018-9145
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