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Deep Reinforcement Learning with Guaranteed Performance - 9783030333836

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.

Price: 88.78 GBP

Location: Aldershot

End Time: 2024-11-03T09:05:26.000Z

Shipping Cost: 38.11 GBP

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Deep Reinforcement Learning with Guaranteed Performance - 9783030333836

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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

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