Description: Deep Reinforcement Learning with Guaranteed Performance Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). A Lyapunov-Based Approach Author(s): Yinyan Zhang, Shuai Li, Xuefeng Zhou Format: Hardback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030333836, 978-3030333836 Synopsis 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.
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Book Title: Deep Reinforcement Learning with Guaranteed Performance
Number of Pages: 225 Pages
Language: English
Publication Name: Deep Reinforcement Learning with Guaranteed Performance: a Lyapunov-Based Approach
Publisher: Springer Nature Switzerland A&G
Publication Year: 2019
Subject: Computer Science
Item Height: 235 mm
Item Weight: 535 g
Type: Textbook
Author: Xuefeng Zhou, Yinyan Zhang, Shuai Li
Subject Area: Mechanical Engineering
Series: Studies in Systems, Decision and Control
Item Width: 155 mm
Format: Hardcover