Journal ArticleDOI
Successful adaptive control of paper machines
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TLDR
An algorithm has been developed which has not only decreased the output variance but also reduced the losses at quality changes and mill set-ups and the general nature of the algorithm permits application to many other types of processes.About:
This article is published in Automatica.The article was published on 1975-01-01. It has received 77 citations till now. The article focuses on the topics: Adaptive control & Optimal control.read more
Citations
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Theory and applications of adaptive control-A survey
TL;DR: It is shown that adaptive control laws can also be obtained from stochastic control theory, and different approaches are discussed with particular emphasis on model reference adaptive systems and self-tuning regulators.
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Paper: Theory and applications of self-tuning regulators
TL;DR: The regulator algorithms, their theory and industrial applications are reviewed and the major ideas are covered but detailed analysis is given elsewhere.
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Adaptive feedback control
TL;DR: Early ideas which primarily attempt to compensate for gain variations and more general methods like gain scheduling, model reference adaptive control, and self-tuning regulators are reviewed.
Adaptive Feedback Control
TL;DR: Adaptive control is now finding its way into the marketplace after many years of effort as discussed by the authors, and it is shown that adaptive control laws can be obtained using stochastic control theory.
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Stochastic adaptive control methods: a survey
TL;DR: The main part of this paper will cover stochastic adaptive controllers and the problem of dual control is given particular attention.
References
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Journal ArticleDOI
System identification-A survey
Karl Johan Åström,Pieter Eykhoff +1 more
TL;DR: The survey explains the least squares method and several of its variants which may solve the problem of correlated residuals, viz. repeated and generalized least squares, maximum likelihood method, instrumental variable method, tally principle.
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On self tuning regulators
TL;DR: In this paper, the problem of controlling a system with constant but unknown parameters is considered and an algorithm obtained by combining a least squares estimator with a minimum variance regulator computed from the estimated model is analyzed.
Journal ArticleDOI
Adaptive control of linear stochastic systems
TL;DR: In this article, an adaptive control algorithm for linear systems with unknown constant parameters and quadratic performance criterion has been obtained, where the control is nonlinear in the estimate of the state of the plant and is given as the weighted integral of the model conditional optimal controls with the a-posteriori probabilities as weights.
An approach to adaptive control using real time identification
TL;DR: An adaptive controller consisting of a real time identifier and a minimum variance regulator is discussed and the behaviour of the adaptive controller is illustrated in two examples.