Efficient predictive model-based and fuzzy control for green urban mobility

Research output: ThesisDissertation (TU Delft)

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In this thesis, we develop efficient predictive model-based control approaches, including model-predictive control (MPC) andmodel-based fuzzy control, for application in urban traffic networks with the aim of reducing a combination of the total time spent by the vehicles within the network and the total emissions. The thesis includes three main parts, where in the first part the main focus is on accurate approaches for estimating the macroscopic traffic variables, such as the temporal-spatial averages, from a microscopic point-of-view. The second part includes efficient approaches for solving the optimization problem of the nonlinear MPC controller. The third and last part of the thesis proposes an adaptive and predictivemodel-based type-2 fuzzy control scheme that can be implementedwithin amulti-agent control architecture.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • Hellendoorn, J., Supervisor
  • Papageorgiou, M, Supervisor, External person
Award date22 Jun 2017
Print ISBNs978-90-5584-224-7
Publication statusPublished - 2017

Bibliographical note

TRAIL Thesis Series T2017/6, the Netherlands TRAIL Research School


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