The extremely low frequency (ELF) electromagnetic field of underwater vehicles originates from multiple coupled sources, yet conventional control strategies typically focus on isolated optimization of individual sources, which limits their effectiveness under complex and dynamic detection scenarios. To address these limitations, this paper proposes a collaborative control method that integrates contribution rate analysis with multi-dimensional utility optimization. A system-level framework is established in which the contribution rate quantifies the relative importance of each electromagnetic source in a given operational scenario. Multi-dimensional utility aggregation is then employed to construct mapping functions between independent control factors and their corresponding control utilities, and the contribution rates are incorporated as weights to formulate a unified composite utility objective function. A multi-objective particle swarm optimization algorithm is applied to determine the optimal control strategy that minimizes the composite utility under dynamic and mission constraints. Simulations based on representative scenarios demonstrate that the proposed collaborative strategy reduces the composite utility by 43.33%, thereby improving the overall control effectiveness compared with conventional approaches. These findings provide a system-level, scene-adaptive active control framework for managing ELF electromagnetic fields of underwater vehicles.
 

extremely low frequency electromagnetic field,collaborative control,multi-dimensional utility optimization,multi-objective particle swarm optimization