本文基于一种UUV艇型，对其进行改进设计，使之有效兼顾水面航态，并建立快速性、操纵性和主要功能的优化数学模型。改进优化软件，使用遗传、混沌和粒子群3种优化算法进行不同代数的优化计算，总结了3种算法的计算原理，比较各个计算代数计算结果的适应度函数最大值，得出最佳参数，并分析了3种算法对约束程度的满足要求。结果表明，粒子群算法相对更优，更易满足约束条件，计算结果为该艇型的水下无人艇的开发研究提供参考依据。
Based on an unmanned underwater vehicle, this paper improves its design, make it effectively take into account the surface navigation state, andestablishes the optimization mathematical model of rapidity, maneuverability and functionality, improves the optimization software, uses genetic, chaos and particle swarm optimization algorithms to carry out different algebra optimization calculation, summarizes the calculation principle of the three algorithms, and compares the fitness function of each calculation algebra calculation result Maximum, the best parameters are obtained, and the three algorithms are analyzed to meet the constraints. The results show that the particle swarm optimization algorithm is relatively better and easier to meet the constraints. The calculation results provide a reference for the development and research of the submarine unmanned vehicle.
2020,42(12): 36-40 收稿日期：2020-01-04
DOI：10.3404/j.issn.1672-7649.2020.12.007
分类号：U664
基金项目：国家自然科学基金资助项目（51379094）；2019年江苏省研究生实践创新计划（SJCX19_1184）
作者简介：程占元(1995-),男,硕士研究生,研究方向为船舶与海洋结构物流体性能
参考文献：
[1] 陈鹏. 水下无人艇结构力学特性和性能综合优化初步研究[D]. 镇江：江苏科技大学, 2013.
CHEN Peng. A preliminary study on the comprehensive optimization of mechanical properties and properties of underwater unmanned craft [D]. Zhenjiang: Jiangsu University of Science and Technology, 2013.
[2] 邹启杰. 基于多目标决策的USV系统可变自主实现机制研究[D].哈尔滨：哈尔滨工程大学, 2014.
QI jie Zou. Research on variable autonomous realization mechanism of USV system based on multi-objective decision-making [D]. Harbin: Harbin Engineering University, 2014.
[3] 魏子凡, 井升平, 杨松林. 基于改进遗传算法的新型水面无人艇性能综合优化分析[J]. 江苏科技大学学报(自然科学版), 2017, 31(1): 6-11
[4] 尹星月, 闫旭, 刘欣, 等. 基于改进遗传算法的无功优化[J]. 东北电力大学学报, 2014, 34(3): 48-53
YIN Xingyue, YAN Xu, LIU Xin, et al. reactive power optimization based on improved genetic algorithm[J]. Journal of Northeast University of Electric Power, 2014, 34(3): 48-53
[5] 俞强. 深海无人智能潜水器力学性能和能源系统综合优化方法研究[D]. 镇江：江苏科技大学, 2014.
[6] Ch en, Sh un, Frouws, Ko os, Van De Voorde, Ed dy. Simulation-based optimization of ship design for dry bulk vessels[J]. Maritime Economics & Logistics, 2011, 13(2)
[7] ZAKERDOOST H, GHASSEMI H. A multi-level optimization technique based on fuel consumption and energy index in early-stage ship design[J]. Structural & Multidisciplinary Optimization, 2018
[8] 苏玉民, 庞永杰. 潜艇原理[M]. 哈尔滨：哈尔滨工程大学出版社, 2004.
[9] DANIELE Peri. Hybridization of the imperialist competitive algorithm and local search with application to ship design optimization[J]. Computers & Industrial Engineering, 2019: 137
[10] 李素素, 王锡淮. 基于粒子群优化的船舶电力系统经济环境调度[J]. 船电技术, 2019, 39(11): 27-30
[11] 赵翱东, 壮而行. 基于蚁群算法的船舶调度优化研究[J]. 舰船科学技术, 2019, 41(6): 7-9
ZHAO Aodong, ZHUANG Erxing. A Study on Ship Scheduling Optimization Based on Ant Colony Algorithm[J]. Ship Science and Technology, 2019, 41(6): 7-9
[12] 薛敏, 徐海成, 王硕. 基于粒子群优化算法的无人艇路径规划[J]. 中国科技信息, 2018(24): 69-70
[13] 李嘉宁, 刘峰, 姚竞争, 等. 无人潜水器主体多学科多目标设计优化[J]. 哈尔滨工程大学学报, 2019, 40(4): 858-864
LI Jianing, LIU Feng, YAO Jingzheng, et al. Optimization of Multidisciplinary Multi-objective Design of Unmanned Submersible Subject[J]. Journal of Harbin Engineering University, 2019, 40(4): 858-864
[14] 刘曼. 一种水面无人艇艇型优化及远程设计系统初步研究[D]. 2018.
