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Factorizations that Relax the Positive Real Condition in Continuous-time ELS Schemes
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TLDR
This paper proposes Extended Least Squares schemes for ARMAX model identification of continuous-time systems with a relaxed Strictly Positive Real condition for global convergence and state conditions for the persistence of excitation of the regression vectors in the proposed ELS schemes to assure strong consistency and obtain convergence rates.About:
This article is published in IFAC Proceedings Volumes.The article was published on 1990-08-01. It has received 1 citations till now. The article focuses on the topics: Strong consistency.read more
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John Barratt Moore 1941–2013
TL;DR: Moore as mentioned in this paper was an electrical engineer who spent most of his distinguished career at the University of Newcastle and the Australian National University following industrial experience and graduate education in Silicon Valley, California, achieving all honours at a comparatively early age, and was recognized principally for his contributions to the field of control systems.
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Convergence rate of least-squares identification and adaptive control for stochastic systems†
Han-Fu Chen,Lei Guo +1 more
TL;DR: In this paper, the convergence rate of least square identification for the multidimensional ARMAX model is established under some decaying excitation conditions which are satisfied if both input and output do not grow too fast and the attenuating excitation technique is applied.
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Persistence of excitation in linear systems
Michael Green,John B. Moore +1 more
TL;DR: In this paper, the authors develop output reachability characterizations of linear finite dimensional multivariate systems, so as to translate excitation properties of system inputs to excitation property of system outputs, states, or associated regression vectors.
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Persistency excitation in continuous-time systems
Nahum Shimkin,Arie Feuer +1 more
TL;DR: For the class of linear time-invariant single-input continuous systems, the authors find conditions on the input under which the state is persistently exciting for adaptive identification purposes.
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A robust stochastic adaptive controller
Chen Han-Fu,Guo Lei +1 more
TL;DR: In this paper, the adaptive tracking problem is considered for discrete-time stochastic systems consisting of a modeled part being a stable ARMAX process and unmodeled dynamics dominated by a small constant epsilon multiplied by a quantity independent of Epsilon but tending to infinity as the past input, output and noise grows.
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Convergence of continuous time stochastic ELS parameter estimation
TL;DR: In this article, a continuous-time adaptive estimation scheme associated with a class of finite dimensional, time invariant, linear stochastic signal models is presented, and a global convergence theory is given for such schemes under a coloured noise/prefiller positive real condition.