Douglas-Peucker piecewise affine approximation of an optimal fuel consumption problem to apply PANOC

Hongjia Ou, Andreas Themelis, Yuno Tsuyoshi, Taketoshi Kawabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In today's world where complying with the requirements of a green economy is more and more imperative for technological progress, energy and fuel-efficient navigation is a topic of primary importance in industrial engineering. In the particular case of autonomous driving and cruise control, the inherent nonlinearity and complexity of the physical dynamics result in a highly nonconvex control problem, which becomes even more challenging if one is to further account for energy saving constraints. Leveraging on recent advancements, we propose a solution based on PANOC [19], a fast optimization solver which can cope with nonconvex problems and enjoys very low computational requirements, provided that some inner subproblems can be solved at negligible effort. In order to account for this binding requirement of the algorithm, we propose a piecewise affine approximation strategy for the fuel consumption model based on the Douglas- Peucker algorithm [7]. The effectiveness of the approach is showcased with numerical simulations on a real-time adaptive cruise control problem for fuel consumption optimization.

Original languageEnglish
Title of host publicationProceedings of 2022 SICE International Symposium on Control Systems, SICE ISCS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages34-38
Number of pages5
ISBN (Electronic)9784907764746
DOIs
Publication statusPublished - 2022
Event2022 SICE International Symposium on Control Systems, SICE ISCS 2022 - Virtual, Online, Japan
Duration: Mar 8 2022Mar 10 2022

Publication series

NameProceedings of 2022 SICE International Symposium on Control Systems, SICE ISCS 2022

Conference

Conference2022 SICE International Symposium on Control Systems, SICE ISCS 2022
Country/TerritoryJapan
CityVirtual, Online
Period3/8/223/10/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Optimization
  • Computer Vision and Pattern Recognition

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