Multi-agent control of urban transportation networks and of hybrid systems with limited information sharing

Renshi Luo

doi:10.4233/uuid:2792af2d-a3c2-4e94-be5a-35a6e9119af7

Multi-agent control of urban transportation networks and of hybrid systems with limited information sharing

Renshi Luo

Team Bart De Schutter

Research output: Thesis › Dissertation (TU Delft)

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Abstract

This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive control of a class of hybrid systems with limiting information sharing and subject to global hard constraints.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Delft University of Technology
Supervisors/Advisors	De Schutter, B.H.K., Supervisor van den Boom, A.J.J., Advisor
Thesis sponsors	China Scholarship Council
Award date	30 Nov 2016
Publisher	TRAIL Research School
Print ISBNs	978-90-5584-213-1
DOIs	https://doi.org/10.4233/uuid:2792af2d-a3c2-4e94-be5a-35a6e9119af7
Publication status	Published - 2016

Bibliographical note

TRAIL Thesis Series T2016/21, the Netherlands TRAIL Research School

Keywords

multi-agent control
model predictive control
dynamic trafﬁc routing
hybrid systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.4233/uuid:2792af2d-a3c2-4e94-be5a-35a6e9119af7

Thesis for printing_Renshi LuoFinal published version, 1.42 MB

Cite this

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title = "Multi-agent control of urban transportation networks and of hybrid systems with limited information sharing",

abstract = "This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive control of a class of hybrid systems with limiting information sharing and subject to global hard constraints.",

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N1 - TRAIL Thesis Series T2016/21, the Netherlands TRAIL Research School

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N2 - This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive control of a class of hybrid systems with limiting information sharing and subject to global hard constraints.

AB - This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive control of a class of hybrid systems with limiting information sharing and subject to global hard constraints.

KW - multi-agent control

KW - model predictive control

KW - dynamic trafﬁc routing

KW - hybrid systems

UR - http://resolver.tudelft.nl/uuid:2792af2d-a3c2-4e94-be5a-35a6e9119af7

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DO - 10.4233/uuid:2792af2d-a3c2-4e94-be5a-35a6e9119af7

M3 - Dissertation (TU Delft)

SN - 978-90-5584-213-1

T3 - TRAIL Thesis Series

PB - TRAIL Research School

ER -

Multi-agent control of urban transportation networks and of hybrid systems with limited information sharing

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

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