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

Dracopoulos, Dimitris C. and Nichols, Barry D. ORCID: https://orcid.org/0000-0002-6760-6037 (2017) Genetic programming for the minimum time swing up and balance control acrobot problem. Expert Systems, 34 (5). ISSN 1468-0394 (doi:10.1111/exsy.12115)

Full text is not in this repository.

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.

Item Type: Article
Additional Information: Article first published online: 6 JUL 2015. Article number = e12115
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 17305
Useful Links:
Depositing User: Barry Nichols
Date Deposited: 23 Jul 2015 08:53
Last Modified: 30 Apr 2019 08:14
URI: https://eprints.mdx.ac.uk/id/eprint/17305

Actions (login required)

Edit Item Edit Item