dkpy: Robust Control with Structured Uncertainty in Python

TL;DR

dkpy is an open-source Python package that enables robust control analysis and synthesis for systems with structured uncertainties, incorporating tools for model uncertainty characterization from data.

Contribution

This paper introduces dkpy, a new Python toolkit for robust control design and analysis under structured uncertainty, including model uncertainty characterization capabilities.

Findings

Provides robust controller analysis and synthesis tools

Includes model uncertainty characterization from data

Facilitates robust performance evaluation

Abstract

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. $\mu$-analysis and $\mu$-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.