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Robust receding horizon parameterized control for multi‐class freeway networks: A tractable scenario‐based approach
Author(s) -
Liu Shuai,
Sadowska Anna,
Frejo José Ramón D.,
Núñez Alfredo,
Camacho Eduardo F.,
Hellendoorn Hans,
De Schutter Bart
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3500
Subject(s) - parameterized complexity , queue , constraint (computer aided design) , computer science , scheme (mathematics) , control theory (sociology) , mathematical optimization , model predictive control , control (management) , engineering , mathematics , algorithm , artificial intelligence , mechanical engineering , mathematical analysis , programming language
Summary In this paper, we propose a tractable scenario‐based receding horizon parameterized control (RHPC) approach for freeway networks. In this approach, a scenario‐based min–max scheme is used to handle uncertainties. This scheme optimizes the worst case among a limited number of scenarios that are considered. The use of parameterized control laws allows us to reduce the computational burden of the robust control problem based on the multi‐class METANET model w.r.t. conventional model predictive control. To assess the performance of the proposed approach, a simulation experiment is implemented, in which scenario‐based RHPC is compared with nominal RHPC, standard control ignoring uncertainties, and standard control including uncertainties. Here, the standard control approaches refer to state feedback controllers (such as PI‐ALINEA for ramp metering). A queue override scheme is included for extra comparison. The results show that nominal RHPC approaches and standard control ignoring uncertainties may lead to high queue length constraint violations, and including a queue override scheme in standard control may not reduce queue length constraint violations to a low level. Including uncertainties in standard control approaches can obviously reduce queue length constraint violations, but the performance improvements are minor. For the given case study, scenario‐based RHPC performs best as it is capable of improving control performance without high queue length constraint violations. Copyright © 2016 John Wiley & Sons, Ltd.