Genetic programming for the minimum time swing up and balance control acrobot problem

Article


Dracopoulos, D. and Nichols, B. 2017. Genetic programming for the minimum time swing up and balance control acrobot problem. Expert systems. 34 (5). https://doi.org/10.1111/exsy.12115
TypeArticle
TitleGenetic programming for the minimum time swing up and balance control acrobot problem
AuthorsDracopoulos, D. and Nichols, B.
Abstract

This work describes how genetic programming is applied to evolving controllers for the minimum time swing up and inverted balance tasks of the continuous state and action: limited torque acrobot. The best swing-up controller is able to swing the acrobot up to a position very close to the inverted ‘handstand’ position in a very short time, shorter than that of Coulom (2004), who applied the same constraints on the applied torque values, and to take only slightly longer than the approach by Lai et al. (2009) where far larger torque values were allowed. The best balance controller is able to balance the acrobot in the inverted position when starting from the balance position for the length of time used in the fitness function in all runs; furthermore, 47 out of 50 of the runs evolve controllers able to maintain the balance position for an extended period, an improvement on the balance controllers generated by Dracopoulos and Nichols (2012), which this paper is extended from. The most successful balance controller is also able to balance the acrobot when starting from a small offset from the balance position for this extended period.

LanguageEnglish
PublisherWiley
JournalExpert systems
ISSN1468-0394
Publication dates
Online06 Jul 2015
Print03 Oct 2017
Publication process dates
Deposited23 Jul 2015
Submitted2015
Output statusPublished
Additional information

Article first published online: 6 JUL 2015.
Article number = e12115

Digital Object Identifier (DOI)https://doi.org/10.1111/exsy.12115
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