Submersible Position Prediction and Search Model Based on Nonlinear Physical Prediction and NSGA-II Algorithm

Nonlinear physical prediction models and the NSGA-II algorithm also have great application scenarios in location prediction search. In this paper, we take the scenario of position prediction and search after the failure of a submersible as an example. Firstly, the ferrite physical prediction modeling is carried out for the three scenarios of no mechanical failure after loss of connection, with mechanical failure and sinking towards the seabed, and at the buoyancy neutral point. Afterwards, a dual-objective optimization of search probability and search time is implemented using the NSGA-II algorithm, aiming to maximize the search probability and minimize the search time. Finally, the path optimization strategies of the three submersibles when searching in conjunction with each other are verified by simulating the actual scenarios, which provides an important theoretical basis and practical guidance for submersible troubleshooting.