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International Journal of Automotive Technology

, Volume 18, Issue 6, pp 1099–1107 | Cite as

Application of iterative learning control in tracking a Dubin’s path in parallel parking

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Abstract

Intelligent parking assist systems will soon be available for most vehicles on the market. Many optimal parking trajectories and control strategies have been proposed for reverse parking. However, most of these require intensive computation, causing difficulties in practical use. This paper makes use of a classical path planning method to find the shortest parking path, and establishes the possibility of integrating iterative learning control (ILC) to exploit the capability of learning from experience to track the designed path. The effectiveness of the ILC structure is demonstrated by simulation and experiments. Tracking performance is shown to be much improved by using a simple learning control law.

Key words

Parallel parking Dubin’s path Iterative learning control Steering control 

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Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Control System and Instrumentation EngineeringKing Mongkut’s University of Technology ThonburiBangkokThailand

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