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Automatic optimal design of self-righting deck of USV based on combined optimization strategy

机译：基于组合优化策略的USV自右甲板自动优化设计

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摘要

The self-righting deck can improve the survivability of the Unmanned Surface Vessel (USV) in the rough sea states. In order to realize the automatic optimal design of the self-righting deck of USV and improve the optimization efficiency, this paper proposes a design method of self-righting deck based on the combination of particle swarm optimization and sequential quadratic programming. The deck wind resistance and the average value of the righting arm at 90-100 degrees angles of heel and 170-180 degrees angles of heel are taken as the optimization objectives. The parametric modeling of the USV deck is carried out and the design variables are determined. The approximate model is constructed by Radial Basis Functions (RBF) to save the optimization time. The automatic optimization framework is established through ISIGHT intelligent optimization platform by integrating Maxsurf Modeler, Maxsurf Stability, and Excel. The shape optimization of self-righting deck for a 7 Dm USV is taken as an example to verify the effectiveness of the design method and optimization process. The proposed method provides a solution for the automatic optimal design of self-righting deck of different types of unmanned boats.
机译：自右甲板可以改善粗糙海区无人面血管（USV）的活力。为了实现USV的自校正甲板的自动优化设计，提高优化效率，提出了一种基于粒子群优化和顺序二次编程组合的自校正牌设计方法。作为优化目标，将甲板耐风电阻和右侧臂角度为90-100度的鞋跟和170-180度角度的平均值。执行USV DECK的参数建模，并确定设计变量。近似模型由径向基函数（RBF）构成，以节省优化时间。通过集成MaxSurf Modeler，MaxSurf稳定性和Excel，通过iSight智能优化平台建立自动优化框架。采用7 dm USV的自右倾甲板的形状优化作为示例，以验证设计方法和优化过程的有效性。该方法为不同类型无人船的自右甲板自动优化设计提供了一种解决方案。

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