Adaptive Neuro-Fuzzy Based Gain Controller for Erbium-Doped Fiber Amplifiers


YÜCEL M., ÇELEBİ F. V. , Torun M., GÖKTAŞ H. H.

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, vol.17, no.1, pp.15-20, 2017 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 1
  • Publication Date: 2017
  • Doi Number: 10.4316/aece.2017.01003
  • Title of Journal : ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING
  • Page Numbers: pp.15-20

Abstract

Erbium-doped fiber amplifiers (EDFA) must have a flat gain profile which is a very important parameter such as wavelength division multiplexing (WDM) and dense WDM (DWDM) applications for long-haul optical communication systems and networks. For this reason, it is crucial to hold a stable signal power per optical channel. For the purpose of overcoming performance decline of optical networks and long-haul optical systems, the gain of the EDFA must be controlled for it to be fixed at a high speed. In this study, due to the signal power attenuation in long-haul fiber optic communication systems and non-equal signal amplification in each channel, an automatic gain controller (AGC) is designed based on the adaptive neuro-fuzzy inference system (ANFIS) for EDFAs. The intelligent gain controller is implemented and the performance of this new electronic control method is demonstrated. The proposed ANFIS-based AGC-EDFA uses the experimental dataset to produce the ANFIS-based sets and the rule base. Laser diode currents are predicted within the accuracy rating over 98 percent with the proposed ANFIS-based system. Upon comparing ANFIS-based AGC-EDFA and experimental results, they were found to be very close and compatible.