Abstract

Techniques described herein provide for an Intelligent Distributed Model Predictive Control System for Adaptive Underwater Acoustic Communication that integrates distributed model predictive control (DMPC) with machine learning (ML) to dynamically adjust transmission parameters, thereby improving signal reliability and adapting to the underwater environment. By leveraging a distributed architecture, the techniques intelligently manage signal transmission among underwater sensors or clusters of underwater sensors. The subsystems of the system work in unison to predict, optimize, and coordinate communication parameters using advanced ML computations.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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