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Ian R. Petersen
Researcher at Australian National University
Publications - 992
Citations - 24919
Ian R. Petersen is an academic researcher from Australian National University. The author has contributed to research in topics: Quantum & Robust control. The author has an hindex of 67, co-authored 959 publications receiving 22649 citations. Previous affiliations of Ian R. Petersen include University of Cambridge & University of Manchester.
Papers
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Journal ArticleDOI
A Negative Imaginary Lemma and the Stability of Interconnections of Linear Negative Imaginary Systems
TL;DR: A previously established Negative Imaginary Lemma is shown to remain true even if the system transfer function matrix has poles on the imaginary axis, and a necessary and sufficient condition is established for the internal stability of the positive feedback interconnections of negative imaginary systems.
Journal ArticleDOI
Fast machine-learning online optimization of ultra-cold-atom experiments.
P. B. Wigley,P. J. Everitt,A. van den Hengel,John Bastian,M. A. Sooriyabandara,Gordon McDonald,K. S. Hardman,C. D. Quinlivan,P. Manju,Carlos C. N. Kuhn,Ian R. Petersen,Andre N. Luiten,Joseph Hope,Nicholas Robins,Michael R. Hush +14 more
TL;DR: In this article, an online optimization process based on machine learning is applied to the production of Bose-Einstein condensates (BEC), which is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely suboptimal for real experiments.
Journal ArticleDOI
Technical communique: Robust state estimation and model validation for discrete-time uncertain systems with a deterministic description of noise and uncertainty
Andrey V. Savkin,Ian R. Petersen +1 more
TL;DR: The main result is a recursive scheme for constructing an ellipsoidal state estimation set of all states consistent with the measured output and the given noise and uncertainty description.
Journal ArticleDOI
Robustness and risk-sensitive filtering
TL;DR: It is shown that risk-sensitive estimators (including filters) enjoy an error bound which is the sum of two terms, the first of which coincides with an upper bound on the error that one would obtain if one knew exactly the underlying probability model.
Proceedings ArticleDOI
Multi-rate stabilization of multivariable discrete-time linear systems via a limited capacity communication channel
Ian R. Petersen,Andrey V. Savkin +1 more
TL;DR: In this article, the authors present an algorithm for the stabilization of a multi-input/multi-output discrete-time linear system via a limited capacity channel using a deterministic multi-rate state space approach which leads to a nonlinear dynamic feedback controller.