東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Stability enhancement methods of inv...

Zhang, Xin.

Linked to FindBook

Google Book

Amazon

博客來

Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning/ by Xin Zhang ... [et al.].
other author:	Zhang, Xin.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	xiv, 164 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Adaptive backstepping current control of single-phase LCL-grid-connected inverters to improve its large-signal stability in the presence of parasitic resistance uncertainty -- An adaptive dual-loop Lyapunov-based control scheme for a single-phase stand-alone inverter to improve its large-signal stability -- Lyapunov-based control of three-phase stand-alone inverters to improve its large-signal stability with inherent dual control loops and load disturbance adaptivity -- An ellipse-optimized composite backstepping control strategy for a point-of-load inverter to improve its large-signal stability under load disturbance in the shipboard power system -- Stability constraining dichotomy solution based model predictive control for the three phase inverter cascaded with input EMI filter in the MEA -- Composite-bisection predictive control to stabilize the three phase inverter cascaded with input EMI filter in the SPS -- Reinforcement learning based weighting factors' real-time updating scheme for the FCS model predictive control to improve the large-signal stability of inverters.
Contained By:	Springer Nature eBook
Subject:	Electric inverters - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-981-19-7191-4
ISBN:	9789811971914

Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning
Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning[electronic resource] /by Xin Zhang ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xiv, 164 p. :ill., digital ;24 cm.

Introduction -- Adaptive backstepping current control of single-phase LCL-grid-connected inverters to improve its large-signal stability in the presence of parasitic resistance uncertainty -- An adaptive dual-loop Lyapunov-based control scheme for a single-phase stand-alone inverter to improve its large-signal stability -- Lyapunov-based control of three-phase stand-alone inverters to improve its large-signal stability with inherent dual control loops and load disturbance adaptivity -- An ellipse-optimized composite backstepping control strategy for a point-of-load inverter to improve its large-signal stability under load disturbance in the shipboard power system -- Stability constraining dichotomy solution based model predictive control for the three phase inverter cascaded with input EMI filter in the MEA -- Composite-bisection predictive control to stabilize the three phase inverter cascaded with input EMI filter in the SPS -- Reinforcement learning based weighting factors' real-time updating scheme for the FCS model predictive control to improve the large-signal stability of inverters.

This book introduces a family of large-signal stability-based control methods for different power inverters (grid-connected inverter, standalone inverter, single-phase inverter, and three-phase inverter) in practical applications. Power inverters have stability issues, which include the inverter's own instability as well as the inverter's instability in relation to the other power electronic devices in the system (i.e., weak grid and the EMI filter) Most of the stability analyses and solutions are based on small-signal stability technology. Unfortunately, in actuality, the majority of practical instability concerns in power inverter systems are large-signal stability problems, which, when compared to small-signal stability problems, can cause substantial damage to electrical equipment. As a result, researchers must conduct a comprehensive investigation of the large-signal stability challenge and solutions for power inverters. This book can be used as a reference for researchers, power inverters manufacturers, and end-users. As a result, the book will not become obsolete in the near future, regardless of technology advancements.

ISBN: 9789811971914

Standard No.: 10.1007/978-981-19-7191-4doiSubjects--Topical Terms:

3625642
Electric inverters
--Mathematical models.

LC Class. No.: TK7872.I65

Dewey Class. No.: 621.3815322

Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning
LDR:03294nmm a2200325 a 4500 001 2314326
003 DE-He213
005 20221129170353.0
006 m d
007 cr nn 008maaau
008 230902s2023 si s 0 eng d
020 $a 9789811971914 $q (electronic bk.)
020 $a 9789811971907 $q (paper)
024 7 $a 10.1007/978-981-19-7191-4 $2 doi
035 $a 978-981-19-7191-4
040 $a GP $c GP $e rda
041 0 $a eng
050 4 $a TK7872.I65
072 7 $a THR $2 bicssc
072 7 $a TEC031000 $2 bisacsh
072 7 $a THR $2 thema
082 0 4 $a 621.3815322 $2 23
090 $a TK7872.I65 $b S775 2023
245 0 0 $a Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning $h [electronic resource] / $c by Xin Zhang ... [et al.].
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xiv, 164 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Adaptive backstepping current control of single-phase LCL-grid-connected inverters to improve its large-signal stability in the presence of parasitic resistance uncertainty -- An adaptive dual-loop Lyapunov-based control scheme for a single-phase stand-alone inverter to improve its large-signal stability -- Lyapunov-based control of three-phase stand-alone inverters to improve its large-signal stability with inherent dual control loops and load disturbance adaptivity -- An ellipse-optimized composite backstepping control strategy for a point-of-load inverter to improve its large-signal stability under load disturbance in the shipboard power system -- Stability constraining dichotomy solution based model predictive control for the three phase inverter cascaded with input EMI filter in the MEA -- Composite-bisection predictive control to stabilize the three phase inverter cascaded with input EMI filter in the SPS -- Reinforcement learning based weighting factors' real-time updating scheme for the FCS model predictive control to improve the large-signal stability of inverters.
520 $a This book introduces a family of large-signal stability-based control methods for different power inverters (grid-connected inverter, standalone inverter, single-phase inverter, and three-phase inverter) in practical applications. Power inverters have stability issues, which include the inverter's own instability as well as the inverter's instability in relation to the other power electronic devices in the system (i.e., weak grid and the EMI filter) Most of the stability analyses and solutions are based on small-signal stability technology. Unfortunately, in actuality, the majority of practical instability concerns in power inverter systems are large-signal stability problems, which, when compared to small-signal stability problems, can cause substantial damage to electrical equipment. As a result, researchers must conduct a comprehensive investigation of the large-signal stability challenge and solutions for power inverters. This book can be used as a reference for researchers, power inverters manufacturers, and end-users. As a result, the book will not become obsolete in the near future, regardless of technology advancements.
650 0 $a Electric inverters $x Mathematical models. $3 3625642
650 0 $a Lyapunov functions. $3 596346
650 1 4 $a Electrical Power Engineering. $3 3592498
650 2 4 $a Electronic Circuits and Systems. $3 3538814
650 2 4 $a Control and Systems Theory. $3 3381515
700 1 $a Zhang, Xin. $3 996620
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-19-7191-4
950 $a Energy (SpringerNature-40367)