Clustering Techniques for Stable Linear Dynamical Systems with applications to Hard Disk Drives
Abstract
In Robust Control and Data Driven Robust Control design methodologies, multiple plant transfer functions or a family of transfer functions are considered and a common controller is designed such that all the plants that fall into this family are stabilized. Though the plants are stabilized, the controller might be sub-optimal for each of the plants when the variations in the plants are large. This paper presents a way of clustering stable linear dynamical systems for the design of robust controllers within each of the clusters such that the controllers are optimal for each of the clusters. First a k-medoids algorithm for hard clustering will be presented for stable Linear Time Invariant (LTI) systems and then a Gaussian Mixture Models (GMM) clustering for a special class of LTI systems, common for Hard Disk Drive plants, will be presented.
Cite
@article{arxiv.2311.10322,
title = {Clustering Techniques for Stable Linear Dynamical Systems with applications to Hard Disk Drives},
author = {Nikhil Potu Surya Prakash and Joohwan Seo and Jongeun Choi and Roberto Horowitz},
journal= {arXiv preprint arXiv:2311.10322},
year = {2023}
}
Comments
6 pages, 4 figures