Skip to main navigation Skip to search Skip to main content

A norm optimal iterative learning control based train trajectory tracking approach

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

4 Citations (Scopus)

Abstract

A norm optimal iterative learning control (NOILC) is proposed and applied in train trajectory tracking problem, and it then is extended to the cases with traction/braking constraint. Rigorous theoretical analysis has shown that the proposed approach can guarantee the asymptotic convergence of train speed and position to desired profiles as iteration number goes infinity. Simulation results further demonstrate the effectiveness of the proposed NOILC approach.
Original languageEnglish
Title of host publicationnan
PublisherInstitute of Electrical and Electronics Engineers Inc.
DOIs
Publication statusPublished - 4 Feb 2013
Event2012 IEEE 51st IEEE Conference on Decision and Control (CDC) - Maui
Duration: 10 Dec 201213 Dec 2012

Conference

Conference2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
CityMaui
Period10/12/1213/12/12
Other2012 IEEE 51st IEEE Conference on Decision and Control (CDC) (10/12/2012-13/12/2012, Maui)

Keywords

  • iterative methods

Fingerprint

Dive into the research topics of 'A norm optimal iterative learning control based train trajectory tracking approach'. Together they form a unique fingerprint.

Cite this