Genetic programming for the minimum time swing up and balance control acrobot problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Dracopoulos:2015:EXSY,
-
author = "Dimitris C. Dracopoulos and Barry D. Nichols",
-
title = "Genetic programming for the minimum time swing up and
balance control acrobot problem",
-
journal = "Expert Systems",
-
year = "2017",
-
volume = "34",
-
number = "5",
-
pages = "e12115",
-
month = oct,
-
ISSN = "1468-0394",
-
URL = "http://dx.doi.org/10.1111/exsy.12115",
-
DOI = "doi:10.1111/exsy.12115",
-
keywords = "genetic algorithms, genetic programming, artificial
intelligence, control systems, computational
intelligence",
-
size = "9 pages",
-
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.",
- }
Genetic Programming entries for
Dimitris C Dracopoulos
Barry D Nichols
Citations