P
Pramod P. Khargonekar
Researcher at University of California, Irvine
Publications - 427
Citations - 26832
Pramod P. Khargonekar is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Linear system & Control theory. The author has an hindex of 64, co-authored 416 publications receiving 25697 citations. Previous affiliations of Pramod P. Khargonekar include University of Michigan & Iowa State University.
Papers
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State-space solutions to standard H/sub 2/ and H/sub infinity / control problems
TL;DR: In this article, simple state-space formulas are derived for all controllers solving the following standard H/sub infinity / problem: for a given number gamma > 0, find all controllers such that the H/ sub infinity / norm of the closed-loop transfer function is (strictly) less than gamma.
Proceedings ArticleDOI
State-space solutions to standard H 2 and H ∞ control problems
TL;DR: In this article, simple state-space formulas are presented for a controller solving a standard H∞-problem, where the controller has the same state-dimension as the plant, its computation involves only two Riccati equations, and it has a separation structure reminiscent of classical LQG theory.
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Robust stabilization of uncertain linear systems: quadratic stabilizability and H/sup infinity / control theory
TL;DR: In this paper, the problem of robustly stabilizing a linear uncertain system is considered with emphasis on the interplay between the time-domain results on the quadratic stabilization of uncertain systems and the frequency domain results on H/sup infinity / optimization.
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Filtering and smoothing in an H/sup infinity / setting
TL;DR: In this paper, the problems of filtering and smoothing are considered for linear systems in an H/sup infinity / setting, i.e. the plant and measurement noises have bounded energies (are in L/sub 2/), but are otherwise arbitrary.
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Mixed H/sub 2//H/sub infinity / control: a convex optimization approach
TL;DR: It is shown that in the state-feedback case one can come arbitrarily close to the optimal (even over full information controllers) mixed H/sub 2//H/sub infinity / performance measure using constant gain state feedback.