Clustering Techniques for Stable Linear Dynamical Systems with
  applications to Hard Disk Drives
Nikhil Potu Surya Prakash Joohwan Seo Jongeun Choi Roberto Horowitz
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.