Optimal Control of SOAs With Artificial Intelligence for Sub-Nanosecond Optical Switching
| Autor: | Zacharaya Shabka, Bawang Goh, W. Konrad Chlupka, Georgios Zervas, Christopher W. F. Parsonson |
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| Rok vydání: | 2020 |
| Předmět: |
Signal Processing (eess.SP)
Optical amplifier Circuit switching Computer science business.industry Particle swarm optimization 020206 networking & telecommunications Systems and Control (eess.SY) 02 engineering and technology Optimal control Electrical Engineering and Systems Science - Systems and Control Optical switch Atomic and Molecular Physics and Optics 020210 optoelectronics & photonics Control theory Genetic algorithm FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Overshoot (signal) Artificial intelligence Electrical Engineering and Systems Science - Signal Processing business |
| Zdroj: | Journal of Lightwave Technology. 38:5563-5573 |
| ISSN: | 1558-2213 0733-8724 |
| Popis: | 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. This manuscript was accepted for publication in the IEEE/OSA Journal of Lightwave Technology on 21st June 2020. Open access code: https://github.com/cwfparsonson/soa_driving Open access data: https://doi.org/10.5522/04/12356696.v1 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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