Parsonson, CWF;
Shabka, Z;
Chlupka, WK;
Goh, B;
Zervas, G;
(2020)
Optimal Control of SOAs With Artificial Intelligence for Sub-Nanosecond Optical Switching.
Journal of Lightwave Technology
, 38
(20)
pp. 5563-5573.
10.1109/JLT.2020.3004645.
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Abstract
Novel approaches to switching ultra-fast semiconductor optical amplifiers using artificial intelligence algorithms (particle swarm optimisation, ant colony optimisation, and a genetic algorithm) are developed and applied both in simulation and experiment. Effective off-on switching (settling) times of 542 ps are demonstrated with just 4.8% overshoot, achieving an order of magnitude improvement over previous attempts described in the literature and standard dampening techniques from control theory.
Type: | Article |
---|---|
Title: | Optimal Control of SOAs With Artificial Intelligence for Sub-Nanosecond Optical Switching |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/JLT.2020.3004645 |
Publisher version: | https://doi.org/10.1109/JLT.2020.3004645 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Ant colony optimisation, artificial intelligence, data centre networks, genetic algorithm, optical interconnects, optical networks, optical switching, particle swarm optimisation, semiconductor optical amplifiers |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10113485 |




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