Abstract
Iterative Learning Control (ILC) is a control technique used to improve performance in repetitive processes. ILC has grown in popularity in part due to its ease of implementation and ability to achieve high levels of accuracy even in complex nonlinear systems. However, a fundamental limitation of ILC is that it relies on system repetition, making the impact of non-repetitive disturbances (e.g., noise) on the controller's performance severe. Much work has been done to reject noise in the time domain; however, little has been done to address noise which is spatial in nature. In this work, a method for limiting noise in spatial signals, which are not uniformly sampled over the spatial domain, is presented within a Norm-Optimal ILC (NO-ILC) framework. The method relies on special construction of the weighting matrices within the NO-ILC cost function, and is applied to Single Point Incremental Sheet Forming, which is inherently spatial in nature. The results show a significant improvement of the filtered signal quality when compared to more conventional matrix construction techniques.
Recommended Citation
J. D. Fischer et al., "Construction of Spatial Filtering Matrices for Norm-Optimal ILC in Single Point Incremental Forming," IFAC-PapersOnLine, vol. 54, no. 20, pp. 482 - 487, Elsevier; International Federation of Automatic Control (IFAC), Nov 2021.
The definitive version is available at https://doi.org/10.1016/j.ifacol.2021.11.219
Department(s)
Mechanical and Aerospace Engineering
Publication Status
Full Text Access
Keywords and Phrases
Disturbance Rejection; Iterative Methods; Learning Control; Single Point Incremental Forming
International Standard Serial Number (ISSN)
2405-8963
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Elsevier; International Federation of Automatic Control (IFAC), All rights reserved.
Publication Date
01 Nov 2021
