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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.

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Singular Perturbation Approximations for General Linear Quantum Systems

TL;DR: In this article, the authors considered the use of singular perturbation approximations for general linear quantum systems where the system dynamics are described in terms of both annihilation and creation operators.
Proceedings ArticleDOI

Quantum Filtering for a Qubit System Subject to Classical Disturbances

TL;DR: The quantum concatenation product is adopted to describe the quantum system which contains both the qubit subsystem and the cavity subsystem, and a stochastic master equation, which provides estimates for the quantum state and the classical signal is given.
Proceedings Article

Multi-variable velocity feedback controller for piezoelectric tube scanner: A “mixed” negative-imaginary and small-gain approach

TL;DR: In this paper, a multi-input multi-output (MIMO) velocity feedback controller (VFC) based on a mixed negative-imaginary and small-gain approach to damp the first resonant mode of a piezoelectric tube scanner (PTS) used in atomic force microscopes (AFMs) is presented.
Proceedings ArticleDOI

Multivariable control of noise in an acoustic duct

TL;DR: A minimax LQG control approach is used to synthesize a controller which minimizes noise level at a specified location in an acoustic duct that is robust against uncertainties introduced by neglecting the higher order modes of the duct.
Journal ArticleDOI

Brief Paper: Almost Optimal LQ-Control Using Stable Periodic Controllers

TL;DR: It is shown that for the existence of such a controller, it is sufficient that the plant be stabilizable and detectable and the control law is required to be almost optimal with respect to a quadratic performance index.