Models used for control design are, to some degree, uncertain. Model uncertainty must be accounted for to ensure the robustness of the closed-loop system. μ-analysis and μ-synthesis methods allow for the analysis and design of controllers subject to structured uncertainties. Moreover, these tools can be applied to robust performance problems as they are fundamentally robust control problems with structured uncertainty. The contribution of this paper is dkpy, an open-source Python package for performing robust controller analysis and synthesis for systems subject to structured uncertainty. dkpy also provides tools for performing model uncertainty characterization using data from a set of perturbed systems. The open-source project can be found at https://github.com/decargroup/dkpy.
@article{arxiv.2511.13927,
title = {dkpy: Robust Control with Structured Uncertainty in Python},
author = {Timothy Everett Adams and Steven Dahdah and James Richard Forbes},
journal= {arXiv preprint arXiv:2511.13927},
year = {2025}
}