As a complex process, wireless optical communication of autonomous underwater vehicles (AUVs) is particularly challenging in the complex communication environment. Therefore, the existing control or denoise systems show some limitations for communication system of multi-AUV. It is still difficult to balance between the complexity of underwater environment and the performance of reality or estimation. This paper is about to investigate the possibility of combining this realistic communication environment for AUVs with existing strategies in fuzzy control framework. More specifically, first, a model for underwater wireless optical communication (UWOC) is proposed, then, signal restore model for UWOC based on fuzzy control is developed for simulation and analysis purposes. To illustrate the superiority of the proposed methods, several common denoising methods are experimented and compared together. It is also shown that the fuzzy control for signal restore model can well adapt to the real communication environment, and ensure more efficiency and stabilization.

作为一个复杂的过程，自动驾驶水下航行器（AUV）的无线光通信在复杂的通信环境中尤其具有挑战性。因此，现有的控制或降噪系统对多AUV的通信系统显示出一些限制。仍然难以在水下环境的复杂性与现实或估计的性能之间取得平衡。本文将探讨将这种现实的AUV通信环境与模糊控制框架中现有策略相结合的可能性。更具体地说，首先，提出了水下无线光通信（UWOC）模型，然后，出于仿真和分析目的，开发了基于模糊控制的UWOC信号恢复模型。为了说明所提出方法的优越性，对几种常见的降噪方法进行了实验并进行了比较。结果表明，信号恢复模型的模糊控制能很好地适应实际的通信环境，并能保证更高的效率和稳定性。