Invasive weed optimization of swing-up control parameters for robot gymnast

Ismail, Hafizul ORCID: https://orcid.org/0000-0002-9594-3700, Eldukhri, Eldaw Elzaki and Packianather, Michael Sylvester ORCID: https://orcid.org/0000-0002-9436-8206 2014. Invasive weed optimization of swing-up control parameters for robot gymnast. Presented at: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Besançon, France, 8-11 July 2014. 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). 2014 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM). Hoboken, NJ: IEEE, pp. 88-93. 10.1109/AIM.2014.6878052

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Abstract

In this paper Invasive Weed Optimization (IWO) was used to investigate the optimum values of the control parameters for the swing up of the Robogymnast. The Robogymnast is classified as an underactuated triple link pendulum. It was developed to study control problems associated with inverted pendulums. Like most underactuated robots the Robogymnast was built to exploit the natural dynamics of the mechanism. It mimics the human acrobat who hangs from a high bar and tries to swing-up to an upside-down position with his/her hands still on the bar. Two motors located on joint 2 (hips) and joint 3 (knees) control the movement of the mechanism. Joint 1 (hands/arms) is firmly attached to a freely rotating high bar mounted on ball bearings. IWO is used to optimize the swing up motion of the robot by determining the optimum values of parameters that control the input sinusoidal voltage of the two motors. The values obtained from IWO are then applied to both simulation and experiment. Results showed that the swing up of the Robogymnast from the stable downwards position to the inverted configuration was successfully achieved.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher:	IEEE
ISBN:	9781479957361
Last Modified:	01 Nov 2022 10:44
URI:	https://orca.cardiff.ac.uk/id/eprint/92725

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