@inbook{479f2e58d7994223bbd9242d0fb01141,
title = "Stochastic Lagrangian Adaptation",
abstract = "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.",
keywords = "Adaptive Control, Optimization, Probability Theory, Stochastic Lagrangian Adaptation, Stochastic Systems",
author = "David Levanony and Caines, \{Peter E.\}",
note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",
year = "2024",
month = jan,
day = "1",
doi = "10.1007/978-3-031-73758-9",
language = "English",
series = "SpringerBriefs in Mathematics",
publisher = "Springer Science and Business Media B.V.",
pages = "1--74",
booktitle = "SpringerBriefs in Mathematics",
address = "Germany",
}