Clustering Techniques for Stable Linear Dynamical Systems with applications to Hard Disk Drives

Autor:	Prakash, Nikhil Potu Surya, Seo, Joohwan, Choi, Jongeun, Horowitz, Roberto
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Systems and Control Computer Science - Artificial Intelligence Computer Science - Machine Learning Mathematics - Dynamical Systems Mathematics - Optimization and Control
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.10322 Zobrazit plný text záznamu View this record from Arxiv