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Parameter-Constrained Adaptive Control

Under certain conditions, parameter constraints that impose a priori information about the open-loop system can dramatically improve the performance of explicit adaptive controllers. Under other conditions, the constraints can actually decrease performance. First, this paper presents a novel paramet...

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Bibliographic Details
Published in:Industrial & engineering chemistry research 1997-11, Vol.36 (11), p.4894-4905
Main Authors: Timmons, W. D, Chizeck, H. J, Casas, F, Chankong, V, Katona, P. G
Format: Article
Language:English
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Summary:Under certain conditions, parameter constraints that impose a priori information about the open-loop system can dramatically improve the performance of explicit adaptive controllers. Under other conditions, the constraints can actually decrease performance. First, this paper presents a novel parameter-constrained identifier on the basis of an efficient, quadratic program solver applied semirecursively, making it ideal for real-time adaptive control. Second, several useful linear constraints for second-order ARMAX models are provided, along with a few examples of their development. Third, the algorithm and the constraints are applied to a benchmark model to explore several conditions, summarized as six guidelines, under which parameter constraints improve or worsen adaptive control. In this last part, it is shown that common orthogonal projection can produce poor results. It is also shown that a priori information is increasingly valuable as excitation decreases and that it is especially useful for adaptive control when combined with re-identification techniques. These results are then applied to the pharmacological control of a time-varying second-order ARMAX model of blood pressure.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie9606597