Optimal Control of SOAs with Artificial Intelligence for Sub-Nanosecond Optical Switching

TL;DR

This paper presents AI-based control methods for ultra-fast semiconductor optical amplifiers, achieving sub-nanosecond switching with minimal overshoot, significantly outperforming previous techniques in simulation and experiments.

Contribution

It introduces novel AI algorithms for controlling SOAs, demonstrating superior switching speed and stability over existing methods through simulation and experimental validation.

Findings

Achieved 542 ps switching time with 4.8% overshoot

Demonstrated order of magnitude improvement over previous methods

Validated effectiveness through both simulation and experimental results

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.