Model predictive control using dual prediction horizons for lateral control

Bo Ah Kim, Young Seop Son, Seung Hi Lee, Chung Choo Chung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

In this paper, we present model predictive control having dual prediction horizons to reduce the length of prediction horizon and obtain the optimal solution rapidly. If prediction horizon is long, it is easy to get optimal solution while assuring closed-loop system stability. Realtime solution is, however, very difficult to calculate within the sample time because the system has complex formulations involving many constraints. On other hand, if prediction horizon is very short, computation overhead is reduced but the stability and performance of closed-loop system are not guaranteed. In this paper, the proposed method reduces the length of prediction horizon as well as maintains the stability and performance. The comparison of performances between the conventionalmethod and the proposed control method are validated via simulations.

Original languageEnglish
Title of host publication7th IFAC Symposium on Intelligent Autonomous Vehicles, IAV 2013 - Proceedings
PublisherIFAC Secretariat
Pages280-285
Number of pages6
EditionPART 1
ISBN (Print)9783902823366
DOIs
StatePublished - 2013
Event8th IFAC Symposium on Intelligent Autonomous Vehicles, IAV 2013 - Gold Coast, QLD, Australia
Duration: 26 Jun 201328 Jun 2013

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume8
ISSN (Print)1474-6670

Conference

Conference8th IFAC Symposium on Intelligent Autonomous Vehicles, IAV 2013
Country/TerritoryAustralia
CityGold Coast, QLD
Period26/06/1328/06/13

Keywords

  • Autonomous vehicles
  • Constraint problems
  • Optimal control
  • Prediction method
  • Predictive control

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