Performance analysis of the optimized equilibrium optimizer algorithm using linear population size reduction in the...

Area of Science:

• Optical Engineering
• Free-Space Optical Communication
• Adaptive Optics

Background:

• Atmospheric turbulence degrades coherent free-space optical communication (CFSOC) performance.
• Sensor-less adaptive optics (SLAO) systems are crucial for mitigating these effects.
• The effectiveness of SLAO systems relies heavily on their control algorithms.

Purpose of the Study:

• To introduce and evaluate an enhanced control algorithm for SLAO systems.
• To improve the speed, precision, and robustness of wavefront correction in CFSOC.
• To demonstrate the suitability of the proposed algorithm for practical SLAO applications.

Main Methods:

• Development of the optimized equilibrium optimizer (LOEO) algorithm, an enhancement of the equilibrium optimizer (EO).
• Modifications include enhanced control parameters, a linear population size reduction (LPSR) strategy, and a revised search framework.
• Theoretical analysis and numerical simulations were conducted to validate the algorithm's performance.

Main Results:

• The LOEO algorithm demonstrated superior precision, rapid correction speed, and strong robustness compared to existing methods.
• Correction speed was enhanced by approximately 50% over the EO algorithm and 15.92 times faster than the SPGD algorithm.
• Experimental results confirmed the LOEO algorithm's efficiency in rectifying distorted wavefront phase aberrations.

Conclusions:

• The LOEO algorithm is a highly effective control strategy for sensor-less adaptive optics systems.
• Its enhanced performance significantly improves the communication capabilities of coherent free-space optical systems.
• The LOEO algorithm presents a promising solution for overcoming atmospheric turbulence challenges in optical communications.