Force control approaches research for robotic machining based on particle swarm optimization and adaptive iteration algorithms
ISSN: 0143-991x
Article publication date: 13 December 2017
Issue publication date: 2 January 2018
Abstract
Purpose
The purpose of this paper is to reduce the strain and vibration during robotic machining.
Design/methodology/approach
An intelligent approach based on particle swarm optimization (PSO) and adaptive iteration algorithms is proposed to optimize the PD control parameters in accordance with robotic machining state.
Findings
The proposed intelligent approach can significantly reduce robotic machining strain and vibration.
Originality value
The relationship between robotic machining parameters is studied and the dynamics model of robotic machining is established. In view of the complexity of robotic machining process, the PSO and adaptive iteration algorithms are used to optimize the PD control parameters in accordance with robotic machining state. The PSO is used to optimize the PD control parameters during stable-machining state, and the adaptive iteration algorithm is used to optimize the PD control parameters during cut-into state.
Keywords
Acknowledgements
This project is sponsored by National Science and Technology Major Project of China (No. 20152X04005006), Science and Technology Planning Project of Guangdong Province, China (No. 2014B090921004, 2014B090920001, 2015B010918002) and Science and Technology Major Project of Zhongshan city, China (No. 2016F2FC0006).
Citation
Chen, S. and Zhang, T. (2018), "Force control approaches research for robotic machining based on particle swarm optimization and adaptive iteration algorithms", Industrial Robot, Vol. 45 No. 1, pp. 141-151. https://doi.org/10.1108/IR-03-2017-0045
Publisher
:Emerald Publishing Limited
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