| 书目名称 | Stochastic Lagrangian Adaptation |
| 编辑 | David Levanony,Peter E. Caines |
| 视频video | |
| 概述 | The Stochastic Lagrangian Adaptation control‘algorithm is completely recursive.Non-compact unbounded parameter sets are permitted sharply distinguishing the work from standard analyses. The work is ba |
| 丛书名称 | SpringerBriefs in Mathematics |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2024 |
| 关键词 | Stochastic Systems; Adaptive Control; Optimization; Stochastic Lagrangian Adaptation; Probability Theory |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-73758-9 |
| isbn_softcover | 978-3-031-73757-2 |
| isbn_ebook | 978-3-031-73758-9Series ISSN 2191-8198 Series E-ISSN 2191-8201 |
| issn_series | 2191-8198 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 16:09:29
