Deep reinforcement learning with guaranteed performance : a Lyapunov-based approach / Yinyan Zhang, Shuai Li, Xuefeng Zhou.
Zhang, Yinyan, author.; Li, Shuai, 1983- author.; Zhou, Xuefeng, author.
2020
QA402.3
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Deep reinforcement learning with guaranteed performance : a Lyapunov-based approach / Yinyan Zhang, Shuai Li, Xuefeng Zhou.
Author Zhang, Yinyan, author.
ISBN 9783030333843 (electronic book)
3030333841 (electronic book)
9783030333836
3030333833
DOI https://doi.org/10.1007/978-3-030-33384-3
https://doi.org/10.1007/978-3-030-33
Published Cham, Switzerland : Springer, [2020].
Language English
Description 1 online resource (xvii, 225 pages) : illustrations.
Item Number 10.1007/978-3-030-33384-3 doi
10.1007/978-3-030-33
Call Number QA402.3
Dewey Decimal Classification 629.8/312
Summary 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 redundant 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed November 13, 2019).
Added Author Li, Shuai, 1983- author.
Zhou, Xuefeng, author.
Series Studies in systems, decision and control ; v. 265.
Available in Other Form Print version: 9783030333836
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
A Survey of Near-Optimal Control of Nonlinear Systems
Near-Optimal Control with Input Saturation
Adaptive Near-Optimal Control with Full-State Feedback
Adaptive Near-Optimal Control Using Sliding Mode
Model-Free Adaptive Near-Optimal Tracking Control
Adaptive Kinematic Control of Redundant Manipulators
Redundancy Resolution with Periodic Input Disturbance.

Browse Subjects

Show more subjects...

Statistics

from
to
Export