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In Robust Control and Data Driven Robust Control design methodologies,multiple plant transfer functions or a family of transfer functions areconsidered and a common controller is designed such that all the plants thatfall into this family are stabilized. Though the plants are stabilized, thecontroller might be sub-optimal for each of the plants when the variations inthe plants are large. This paper presents a way of clustering stable lineardynamical systems for the design of robust controllers within each of theclusters such that the controllers are optimal for each of the clusters. Firsta k-medoids algorithm for hard clustering will be presented for stable LinearTime Invariant (LTI) systems and then a Gaussian Mixture Models (GMM)clustering for a special class of LTI systems, common for Hard Disk Driveplants, will be presented.

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