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Brian D. O. Anderson
Researcher at Australian National University
Publications - 1120
Citations - 50069
Brian D. O. Anderson is an academic researcher from Australian National University. The author has contributed to research in topics: Linear system & Control theory. The author has an hindex of 96, co-authored 1107 publications receiving 47104 citations. Previous affiliations of Brian D. O. Anderson include University of Newcastle & Eindhoven University of Technology.
Papers
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Proceedings ArticleDOI
Control of acyclic formations of mobile autonomous agents
TL;DR: It is shown that, except for a thin set of initial positions, the gradient-like control law can always cause a formation to converge to a finite limit in an equilibrium manifold for which all distance constraints are satisfied.
Proceedings ArticleDOI
Controlling a triangular formation of mobile autonomous agents
TL;DR: It is shown that the control law can cause any initially non-collinear, positively- oriented triangular formation to converge exponentially fast to a desired positively-oriented, negatively-oriented triangular formation.
Journal ArticleDOI
Recent Advances in the Modelling and Analysis of Opinion Dynamics on Influence Networks
TL;DR: It is identified that for topics whose logical interdependencies take on a cascade structure, disagreement in opinions can occur if individuals have competing and/or heterogeneous views on how the topics are related, i.e., the logical interdependence structure varies between individuals.
Journal ArticleDOI
Frequency tracking of nonsinusoidal periodic signals in noise
TL;DR: In this article, extended Kalman filtering is applied to the problem of estimating the signal's frequency and the amplitudes and phases of the first m harmonic components of a periodic signal measured in noise.
Journal ArticleDOI
Graphical properties of easily localizable sensor networks
Brian D. O. Anderson,Peter N. Belhumeur,Tolga Eren,David K. Goldenberg,A. Stephen Morse,Walter Whiteley,Y. Richard Yang +6 more
TL;DR: This paper identifies graphical properties which can ensure unique localizability, and further sets of properties which could provide guarantees on the associated computational complexity of the sensor network localization problem.