Format:
1 Online-Ressource (VI, 77 Seiten)
ISBN:
9783031737589
Series Statement:
SpringerBriefs in mathematics
Content:
This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive the maximum likelihood estimate into the set of parameters representing the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems.
Note:
Introduction -- Problem Statement -- Asymptotic Maximum Likelihood Identification -- Geometric Results -- Lagrangian Adaptation -- Proof of Theorem 5.2 -- Index.
Additional Edition:
ISBN 9783031737572
Additional Edition:
ISBN 9783031737596
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031737572
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031737596
Additional Edition:
Erscheint auch als Druck-Ausgabe Levanony, David Stochastic Lagrangian adaptation Cham : Springer Nature, 2024 ISBN 9783031737572
Language:
English
Keywords:
Stochastische Kontrolltheorie
;
Adaptivregelung
;
Lagrange-Gleichungen
;
Linearquadratische Kontrolltheorie
;
Maximum-Likelihood-Schätzung
DOI:
10.1007/978-3-031-73758-9
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