國立高雄大學圖資館 |

Language: English

Back

Deep reinforcement learning with gua...

Li, Shuai.

Deep reinforcement learning with guaranteed performancea Lyapunov-based approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep reinforcement learning with guaranteed performanceby Yinyan Zhang, Shuai Li, Xuefeng Zhou.
Reminder of title:	a Lyapunov-based approach /
Author:	Zhang, Yinyan.
other author:	Li, Shuai.
Published:	Cham :Springer International Publishing :2020.
Description:	xvii, 225 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Control theory.
Online resource:	https://doi.org/10.1007/978-3-030-33384-3
ISBN:	9783030333843$q(electronic bk.)

Deep reinforcement learning with guaranteed performancea Lyapunov-based approach /
Zhang, Yinyan.

Deep reinforcement learning with guaranteed performancea Lyapunov-based approach /[electronic resource] :by Yinyan Zhang, Shuai Li, Xuefeng Zhou. - Cham :Springer International Publishing :2020. - xvii, 225 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v.2652198-4182 ;. - Studies in systems, decision and control ;v.3..

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.

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.

ISBN: 9783030333843$q(electronic bk.)

Standard No.: 10.1007/978-3-030-33384-3doiSubjects--Topical Terms:

182248
Control theory.

LC Class. No.: QA402.3 / .Z436 2020

Dewey Class. No.: 629.8312

Deep reinforcement learning with guaranteed performancea Lyapunov-based approach /
LDR:02618nmm a2200337 a 4500 001 574172
003 DE-He213
005 20200317160705.0
006 m d
007 cr nn 008maaau
008 201007s2020 sz s 0 eng d
020 $a 9783030333843$q(electronic bk.)
020 $a 9783030333836$q(paper)
024 7 $a 10.1007/978-3-030-33384-3 $2 doi
035 $a 978-3-030-33384-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402.3 $b .Z436 2020
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
082 0 4 $a 629.8312 $2 23
090 $a QA402.3 $b .Z63 2020
100 1 $a Zhang, Yinyan. $3 801426
245 1 0 $a Deep reinforcement learning with guaranteed performance $h [electronic resource] : $b a Lyapunov-based approach / $c by Yinyan Zhang, Shuai Li, Xuefeng Zhou.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xvii, 225 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.265
505 0 $a 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.
520 $a 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.
650 0 $a Control theory. $3 182248
650 0 $a Lyapunov stability. $3 338007
650 1 4 $a Control and Systems Theory. $3 825946
650 2 4 $a Robotics. $3 181952
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Systems Theory, Control. $3 274654
650 2 4 $a Robotics and Automation. $3 357111
700 1 $a Li, Shuai. $3 799166
700 1 $a Zhou, Xuefeng. $3 861741
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Studies in systems, decision and control ; $v v.3. $3 678532
856 4 0 $u https://doi.org/10.1007/978-3-030-33384-3
950 $a Intelligent Technologies and Robotics (Springer-42732)