9783030333867 - deep reinforcement learning with guaranteed performance: a lyapunov-based approach (studies in systems, decision and control, band 265) von zhang, yinyan; li, shuai; zhou, xuefeng (2 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2020
Serie: Studies in Systems, Decision and Control, Buch 225 von 378. Buch 225 von 378 - Studies in Systems, Decision and Control
- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
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EUR 122,10
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Taschenbuch. Zustand: Neu. Deep Reinforcement Learning with Guaranteed Performance | A Lyapunov-Based Approach | Yinyan Zhang (u. a.) | Taschenbuch | xvii | Englisch | 2020 | Springer | EAN 9783030333867 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]spring…er[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer International Publishing 2020
Serie: Studies in Systems, Decision and Control, Buch 225 von 378. Buch 225 von 378 - Studies in Systems, Decision and Control
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 139,09
EUR 61,88 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redu…ndant manipulators with consideration of parameter uncertainty and periodic disturbances.It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution.Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
