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Design methodology of a mini-missile considering flight performance and guidance precision 被引量:1
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作者 ZHANG Licong GONG Chunlin +1 位作者 SU Hua ANDREA Da Ronch 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2024年第1期195-210,共16页
The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs m... The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach. 展开更多
关键词 mini-missiles(MMs) GUIDANCE NAVIGATION and control(GNC)system multi-objective optimization multidisciplinary design optimization(MDO) flight performance guidance precision
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基于自适应神经网络的火炮身管结构优化研究 被引量:13
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作者 萧辉 杨国来 +2 位作者 孙全兆 葛建立 于清波 《兵工学报》 EI CAS CSCD 北大核心 2017年第10期1873-1880,共8页
针对火炮多学科优化设计存在计算量大、收敛慢和易陷入局部最优的问题,提出一种基于自适应径向基函数(RBF)神经网络的结构优化方法。编程计算火炮高低温压力曲线,并对ABAQUS有限元软件二次开发将其加载进有限元模型以获取身管的优化目标... 针对火炮多学科优化设计存在计算量大、收敛慢和易陷入局部最优的问题,提出一种基于自适应径向基函数(RBF)神经网络的结构优化方法。编程计算火炮高低温压力曲线,并对ABAQUS有限元软件二次开发将其加载进有限元模型以获取身管的优化目标值,构建其与设计变量间自适应RBF神经网络模型。引入罚函数法处理约束条件,采用遗传算法在模型中求解寻优。每次优化迭代时利用建立的局部和全局分析模型分别选取更新点,增加样本点来更新神经网络,以提高神经网络的局部和全局预测能力。采用典型函数算例和某火炮身管结构多目标优化,实例验证了所提出优化策略的有效性。研究结果表明:身管优化后质量减小了6.63%,结构刚度提高了5.60%,最大等效应力减小了6.34%;与仅使用遗传算法相比,该方法所需的有限元模型调用次数降低了86.5%,运行时间减少了83.3%,为火炮结构设计和优化提供了参考。 展开更多
关键词 兵器科学与技术 火炮身管 多学科多目标结构优化 自适应神经网络 再采样策略
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