UNIVERSITAS BINA DARMA, UNIVERSITAS BINA DARMA (2022) LEARNING-BASED HYBRID CONTROL OF CLOSED-KINEMATIC CHAIN ROBOTIC END-EFFECTORS. LEARNING-BASED HYBRID CONTROL OF CLOSED-KINEMATIC CHAIN ROBOTIC END-EFFECTORS.
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Abstract
This paper proposes a control scheme that combines the concepts of hybrid control and learning control for controlling force and position of a six-degree-of-freedom robotic end-effector with closed-kinemat ic chain mechanism, which performs repeatable tasks. The control scheme consists of two control systems: the hybrid control system and the learning control system. The hybrid control system is composed of two feedback loops, a position loop and a force loop, which produce inputs to the end-effector actuators, based on errors in position and contact forces of selected degrees of freedom. The learning control system consisting of two PD-type learning controllers arranged also in a hybrid structure provides addtional inputs to the actuators to improve the end-effector performance after each trial. The paper shows that with proper learning controller gains the actual position and contact force can approach the desired values as the number of trials increases. Experimental studies performed on a two-degree-of�freedom end-effector show that the control scheme provides path tracking with sat isfactory precision while maintaining contact forces with minimal errors after several trials.
| Item Type: | Article |
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| Subjects: | H Social Sciences > H Social Sciences (General) |
| Divisions: | Faculty of Law, Arts and Social Sciences > School of Social Sciences |
| Depositing User: | Mr Edi Surya Negara |
| Date Deposited: | 20 Jun 2022 07:44 |
| Last Modified: | 20 Jun 2022 07:44 |
| URI: | http://eprints.binadarma.ac.id/id/eprint/13640 |
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