摘要
将动力系统阻尼参数识别反问题转化为非线性优化问题处理,提出了基于遗传算法的动力系统阻尼参数识别方法。为了提高简单遗传算法的计算效率和处理早熟问题,将模拟退火算法与遗传算法相结合,建立了混合遗传算法。数值计算结果表明,本文所建立的方法对于求解参数识别反问题和非线性优化问题是非常有效的,并且具有良好的鲁棒性和全局收敛能力。
The inverse problem of parameter identification was transformed into a nonlinear optimization problem. An approach to solving inverse problems was presented for the identification of the damping coefficient in the dynamic system by using genetic algorithm. Genetic algorithm is a global search technique for parameter optimization and parameter identification. In order to enhance computational efficiency and to deal with the premature problem of simple genetic algorithm, the optimization problem is then solved by using a hybrid genetic algorithm. The simulated annealing algorithm and genetic algorithm were combined to produce an adaptive procedure that has the merits of both methods. Results are presented for demonstrating the effectiveness of this approach for solving inverse problem and the characteristics of robustness and global convergence.
出处
《计算力学学报》
EI
CAS
CSCD
北大核心
2004年第5期551-556,共6页
Chinese Journal of Computational Mechanics
基金
国家自然科学基金(10072014)资助项目.
关键词
混合遗传算法
参数识别
阻尼矩阵
精细积分
模拟退火算法
Convergence of numerical methods
Genetic algorithms
Identification (control systems)
Inverse problems
Optimization
Robustness (control systems)
Simulated annealing