Data-driven IQC-Based Uncertainty Modelling for Robust Control Design
A new approach is presented in the paper for modelling uncertainty as an elliptical set for robust controller synthesis. The method involves finding the best linear nominal model and the corresponding elliptical uncertainty set that is consistent with a set of frequency response functions of linear time-invariant (LTI) single-input single-output (SISO) systems. The uncertainty set is then converted into an equivalent integral quadratic constraint (IQC) using a novel split representation of uncertainty. Finally, the IQC is integrated into a data-driven frequency-domain controller synthesis method through convex optimization. The simulation and experimental results demonstrate that the proposed method yields a “tighter” uncertainty set and improved stability margins compared to classical methods that use disk uncertainty.
2023_IFAC_Elliptical-SISO.pdf
Main Document
http://purl.org/coar/version/c_ab4af688f83e57aa
openaccess
CC BY
2.56 MB
Adobe PDF
ff8b59430f096f381f8a1b6295f8c226
2023_07_IFAC_Elliptical_IQC_PPT.pdf
Presentation
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
openaccess
CC BY
1.68 MB
Adobe PDF
13c6768082ee01a881267a82c2e9bc2a