Deters, Christian and Hak-Keung, Lam and Barrett-Baxendale, Mark and Secco, Emanuele Lindo (2015) Model-Based Self-Tuning PI Control of Bolt-Nut Tightening for Wind Turbine Bearing Assembly. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. IEEE, pp. 334-342. ISBN 9781509001538
Full text not available from this repository. (Request a copy)Abstract
"One of the core steps of the assembly of wind turbines is the assembly of the bearings on the wind turbine hub. The hub can contain up to 128 bolt connections to install the bearing blades: nuts need to be precisely tightened to ensure a uniformly distributed clamping force as well as avoiding assembly errors, e.g. nut misalignments. The bolt-nut connection is a non-linear system with uncertainties making it difficult to design a numerical model and PI Gains.
This paper presents a novel two-stage Proportional-Integral (PI) controller with assembly error detection capability for bolt tightening process. It is based on the combination of a numerical model (offline training) and a genetic algorithm (GA) for online training on the physical bolt system. Since the model does not include all non-linearity and uncertainties of the physical plant (here the bolt-nut connection), it is used at first to estimate the range of the PI values; followed by a fine tuning of the values online by the GA.
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| Item Type: | Book Section |
|---|---|
| Keywords: | GA; self-tuning PI control; bolt tightening; self-adaptive manufacturing |
| Faculty / Department: | Faculty of Human and Digital Sciences > Mathematics and Computer Science |
| Depositing User: | Users 23 not found. |
| Date Deposited: | 15 Jan 2016 12:07 |
| Last Modified: | 15 Jan 2016 12:07 |
| URI: | https://hira.hope.ac.uk/id/eprint/691 |
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