02812nam a22005175i 4500 978-3-031-73758-9 DE-He213 20251030113304.0 cr nn 008mamaa 241109s2024 sz | s |||| 0|eng d 9783031737589 978-3-031-73758-9 10.1007/978-3-031-73758-9 doi QA274-274.9 PBT bicssc PBWL bicssc MAT029000 bisacsh PBT thema PBWL thema Levanony, David. author. (orcid)0000-0002-4332-8925 https://orcid.org/0000-0002-4332-8925 aut http://id.loc.gov/vocabulary/relators/aut 87228 Stochastic Lagrangian Adaptation [electronic resource] / by David Levanony, Peter E. Caines. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. VI, 77 p. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Mathematics, 2191-8201 Introduction -- Problem Statement -- Asymptotic Maximum Likelihood Identification -- Geometric Results -- Lagrangian Adaptation -- Proof of Theorem 5.2 -- Index. 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. Stochastic processes. 76770 Stochastic Systems and Control. 87229 Caines, Peter E. author. (orcid)0000-0002-5248-9456 https://orcid.org/0000-0002-5248-9456 aut http://id.loc.gov/vocabulary/relators/aut 87230 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031737572 Printed edition: 9783031737596 SpringerBriefs in Mathematics, 2191-8201 70788 https://doi.org/10.1007/978-3-031-73758-9 ZDB-2-SMA ZDB-2-SXMS 64820 64820