基于混合遗传算法的动力系统阻尼参数识别方法

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。

Identification of the damping coefficients in dynamic system using hybrid genetic algorithm

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 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 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.