語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Traffic congestion control by PDE backstepping
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Traffic congestion control by PDE backstepping/ by Huan Yu, Miroslav Krstic.
作者:
Yu, Huan.
其他作者:
Krstic, Miroslav.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
xvii, 356 p. :ill., digital ; : 24 cm.;
Contained By:
Springer Nature eBook
標題:
Automatic control. -
電子資源:
https://doi.org/10.1007/978-3-031-19346-0
ISBN:
9783031193460
Traffic congestion control by PDE backstepping
Yu, Huan.
Traffic congestion control by PDE backstepping
[electronic resource] /by Huan Yu, Miroslav Krstic. - Cham :Springer International Publishing :2022. - xvii, 356 p. :ill., digital ;24 cm. - Systems & control: foundations & applications,2324-9757. - Systems & control: foundations & applications..
Introduction -- Backstepping for Coupled Hyperbolic PDEs -- Part I: Basic Backstepping Control of Freeway Traffic -- Stabilization of ARZ Model with Known Parameters and Fundamental Diagram -- Observer Validation on Freeway Data -- Adaptive Control of ARZ Traffic Model -- Event-Triggered Control of ARZ Model -- Comparison of Backstepping with Reinforcement Learning -- Part II: Advanced Backstepping for Traffic Flows -- Two-Lane Traffic Control -- Two-Class Traffic Control -- Control of Two-Cascaded Freeway Segments -- Estimation of Freeway Diverge Flows -- Control under Routing-Induced Instability -- Bilateral Regulation of Moving Shock Position -- Extremum Seeking of Downstream Bottleneck.
This monograph explores the design of controllers that suppress oscillations and instabilities in congested traffic flow using PDE backstepping methods. The first part of the text is concerned with basic backstepping control of freeway traffic using the Aw-Rascle-Zhang (ARZ) second-order PDE model. It begins by illustrating a basic control problem - suppressing traffic with stop-and-go oscillations downstream of ramp metering - before turning to the more challenging case for traffic upstream of ramp metering. The authors demonstrate how to design state observers for the purpose of stabilization using output-feedback control. Experimental traffic data are then used to calibrate the ARZ model and validate the boundary observer design. Because large uncertainties may arise in traffic models, adaptive control and reinforcement learning methods are also explored in detail. Part II then extends the conventional ARZ model utilized until this point in order to address more complex traffic conditions: multi-lane traffic, multi-class traffic, networks of freeway segments, and driver use of routing apps. The final chapters demonstrate the use of the Lighthill-Whitham-Richards (LWR) first-order PDE model to regulate congestion in traffic flows and to optimize flow through a bottleneck. In order to make the text self-contained, an introduction to the PDE backstepping method for systems of coupled first-order hyperbolic PDEs is included. Traffic Congestion Control by PDE Backstepping is ideal for control theorists working on control of systems modeled by PDEs and for traffic engineers and applied scientists working on unsteady traffic flows. It will also be a valuable resource for researchers interested in boundary control of coupled systems of first-order hyperbolic PDEs.
ISBN: 9783031193460
Standard No.: 10.1007/978-3-031-19346-0doiSubjects--Topical Terms:
528275
Automatic control.
LC Class. No.: HE336.C64
Dewey Class. No.: 388.3142015118
Traffic congestion control by PDE backstepping
LDR
:03549nam a2200337 a 4500
001
1097930
003
DE-He213
005
20221216202218.0
006
m d
007
cr nn 008maaau
008
230419s2022 sz s 0 eng d
020
$a
9783031193460
$q
(electronic bk.)
020
$a
9783031193453
$q
(paper)
024
7
$a
10.1007/978-3-031-19346-0
$2
doi
035
$a
978-3-031-19346-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HE336.C64
072
7
$a
GPFC
$2
bicssc
072
7
$a
SCI064000
$2
bisacsh
072
7
$a
GPFC
$2
thema
082
0 4
$a
388.3142015118
$2
23
090
$a
HE336.C64
$b
Y94 2022
100
1
$a
Yu, Huan.
$e
author.
$3
1393307
245
1 0
$a
Traffic congestion control by PDE backstepping
$h
[electronic resource] /
$c
by Huan Yu, Miroslav Krstic.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Birkhäuser,
$c
2022.
300
$a
xvii, 356 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Systems & control: foundations & applications,
$x
2324-9757
505
0
$a
Introduction -- Backstepping for Coupled Hyperbolic PDEs -- Part I: Basic Backstepping Control of Freeway Traffic -- Stabilization of ARZ Model with Known Parameters and Fundamental Diagram -- Observer Validation on Freeway Data -- Adaptive Control of ARZ Traffic Model -- Event-Triggered Control of ARZ Model -- Comparison of Backstepping with Reinforcement Learning -- Part II: Advanced Backstepping for Traffic Flows -- Two-Lane Traffic Control -- Two-Class Traffic Control -- Control of Two-Cascaded Freeway Segments -- Estimation of Freeway Diverge Flows -- Control under Routing-Induced Instability -- Bilateral Regulation of Moving Shock Position -- Extremum Seeking of Downstream Bottleneck.
520
$a
This monograph explores the design of controllers that suppress oscillations and instabilities in congested traffic flow using PDE backstepping methods. The first part of the text is concerned with basic backstepping control of freeway traffic using the Aw-Rascle-Zhang (ARZ) second-order PDE model. It begins by illustrating a basic control problem - suppressing traffic with stop-and-go oscillations downstream of ramp metering - before turning to the more challenging case for traffic upstream of ramp metering. The authors demonstrate how to design state observers for the purpose of stabilization using output-feedback control. Experimental traffic data are then used to calibrate the ARZ model and validate the boundary observer design. Because large uncertainties may arise in traffic models, adaptive control and reinforcement learning methods are also explored in detail. Part II then extends the conventional ARZ model utilized until this point in order to address more complex traffic conditions: multi-lane traffic, multi-class traffic, networks of freeway segments, and driver use of routing apps. The final chapters demonstrate the use of the Lighthill-Whitham-Richards (LWR) first-order PDE model to regulate congestion in traffic flows and to optimize flow through a bottleneck. In order to make the text self-contained, an introduction to the PDE backstepping method for systems of coupled first-order hyperbolic PDEs is included. Traffic Congestion Control by PDE Backstepping is ideal for control theorists working on control of systems modeled by PDEs and for traffic engineers and applied scientists working on unsteady traffic flows. It will also be a valuable resource for researchers interested in boundary control of coupled systems of first-order hyperbolic PDEs.
650
0
$a
Automatic control.
$3
528275
650
0
$a
Traffic congestion
$x
Mathematical models.
$3
1065117
700
1
$a
Krstic, Miroslav.
$3
677369
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
830
0
$a
Systems & control: foundations & applications.
$3
882159
856
4 0
$u
https://doi.org/10.1007/978-3-031-19346-0
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入