多体系统
数学
渡线
多项式的
积分器
微分方程
高斯求积
应用数学
数学优化
微分代数方程
控制理论(社会学)
常微分方程
计算机科学
尼氏法
数学分析
控制(管理)
计算机网络
带宽(计算)
人工智能
物理
量子力学
积分方程
标识
DOI:10.1177/1687814015581260
摘要
Based on the general model of design optimization of multibody dynamics, a modified genetic algorithm with adaptive crossover and mutation rates is developed to find optimal design variables which satisfy the dynamic constraints and obtain optimum objective values. Generalized-α projection method and higher order variational integrators with Lagrangian polynomial and Gauss quadrature formula are used to solve differential–algebraic equations during optimization process. Efficiency and accuracy of the numerical results obtained by intelligent design optimization with different differential–algebraic equation solving methods are compared.
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