東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Deep reinforcement learning with gua...

Zhang, Yinyan.

FindBook

Google Book

Amazon

博客來

Deep reinforcement learning with guaranteed performance = a Lyapunov-based approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep reinforcement learning with guaranteed performance/ by Yinyan Zhang, Shuai Li, Xuefeng Zhou.
其他題名:	a Lyapunov-based approach /
作者:	Zhang, Yinyan.
其他作者:	Li, Shuai.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xvii, 225 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Control theory. -
電子資源:	https://doi.org/10.1007/978-3-030-33384-3
ISBN:	9783030333843

Deep reinforcement learning with guaranteed performance = a 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.265..

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

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

535880
Control theory.

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

Dewey Class. No.: 629.8312

Deep reinforcement learning with guaranteed performance = a Lyapunov-based approach /
LDR:02618nmm a2200337 a 4500 001 2214695
003 DE-He213
005 20200317160705.0
006 m d
007 cr nn 008maaau
008 201118s2020 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 3297654
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 535880
650 0 $a Lyapunov stability. $3 705168
650 1 4 $a Control and Systems Theory. $3 3381515
650 2 4 $a Robotics. $3 519753
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Systems Theory, Control. $3 893834
650 2 4 $a Robotics and Automation. $3 1066695
700 1 $a Li, Shuai. $3 3170629
700 1 $a Zhou, Xuefeng. $3 3445454
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in systems, decision and control ; $v v.265. $3 3445455
856 4 0 $u https://doi.org/10.1007/978-3-030-33384-3
950 $a Intelligent Technologies and Robotics (Springer-42732)