Guaranteed $\mathcal{H}_\infty$ performance analysis and controller synthesis for interconnected linear systems from noisy input-state data
Abstract
The increase in available data and complexity of dynamical systems has sparked the research on data-based system performance analysis and controller design. Recent approaches can guarantee performance and robust controller synthesis based on noisy input-state data of a single dynamical system. In this paper, we extend a recent data-based approach for guaranteed performance analysis to distributed analysis of interconnected linear systems. We present a new set of sufficient LMI conditions based on noisy input-state data that guarantees performance and have a structure that lends itself well to distributed controller synthesis from data. Sufficient LMI conditions based on noisy data are provided for the existence of a dynamic distributed controller that achieves performance. The presented approach enables scalable analysis and control of large-scale interconnected systems from noisy input-state data sets.
Cite
@article{arxiv.2103.14399,
title = {Guaranteed $\mathcal{H}_\infty$ performance analysis and controller synthesis for interconnected linear systems from noisy input-state data},
author = {Tom R. V. Steentjes and Mircea Lazar and Paul M. J. Van den Hof},
journal= {arXiv preprint arXiv:2103.14399},
year = {2022}
}