采用遗传算法实现时域模型降阶

提出一种基于遗传算法的时域降阶新方法 ,它可以将高阶的模型降低为典型的二阶系统模型 .通过实际模型和目标模型在时间内的误差 ,将模型的降阶过程转化为最小优化过程 ,最优求解采用遗传算法 .在仿真软件包 Matlab和 Simulink的帮助下 ,先确定遗传算法的搜索空间 ,再建立模型匹配时间响应误差的自动汲取框图 .通过发挥遗传算法的优点和引入添加微变异种群等新策略 ,使得求解具有智能、高效、准确的特点 ,十分适合于工程应用

Realizing Reduction of Time Domain Model by Adopting Genetic Algorithm

A new method based on genetic algorithm is prsented for a time domain model to reduce order by which a model of higher order can be reduced into typical model of second order system. By adopting error in time domain response between actual model and objective model, the model reduction process is transformed into minimal optimization process, which is solved by genetic algorithm. With the help of Matlab and Simulink as the simulation software package, the authors confirm firstly the searched space of genetic algorithm and set up secondly the block diagram of automatic acquisition for the error in time response of model matching. By giving play to strong point of genetic algorithm and leading in such new tactics as slight mutation group, the solving will be intelligent and efficient and accurate, and will be quite suitable for the applicataion to engineering.