Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
696842 | Automatica | 2008 | 6 Pages |
Abstract
In this paper we consider a unified framework for parameter estimation problems. Under this framework, the unknown parameters appear in a linear fractional transformation (LFT). A key advantage of the LFT problem formulation is that it allows us to efficiently compute gradients, Hessians, and Gauss–Newton directions for general parameter estimation problems without resorting to inefficient finite-difference approximations. The generality of this approach also allows us to consider issues such as identifiability, persistence of excitation, and convergence for a large class of model structures under a single unified framework.
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Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Kenneth Hsu, Tyrone Vincent, Greg Wolodkin, Sundeep Rangan, Kameshwar Poolla,