基于遗传算法的电动静液作动器模型参数辨识
发布时间：2018-10-16 21:57
【摘要】：电动静液作动器具有功率密度高,集成度高以及高效节能等优点。为了获得较为精确的作动器线性数学模型,采用了遗传算法对模型参数进行辨识。在遗传算法中,将一组模型参数值视为一个染色体的基因编码,以实测的系统频率响应数据作为评价染色体优劣的标准,并构造相应的适应度函数。通过使用基于排序的选择概率设定方法,算术交叉算子以及高斯变异算子,并进行迭代运算,实现了种群的遗传进化操作与对最优解的搜索。最终的辨识结果证明了遗传算法辨识作动器模型参数的有效性。
[Abstract]:Electric hydrostatic actuator has the advantages of high power density, high integration and high efficiency and energy saving. In order to obtain a more accurate linear mathematical model of actuator, genetic algorithm is used to identify the parameters of the model. In genetic algorithm, a set of model parameters is regarded as the gene coding of a chromosome, and the measured system frequency response data is taken as the criterion to evaluate the chromosomes, and the corresponding fitness function is constructed. The selection probability setting method based on sorting, arithmetic crossover operator and Gao Si mutation operator are used to carry out iterative operation to realize the genetic evolution operation of population and the search for the optimal solution. The final identification results demonstrate the effectiveness of genetic algorithm in identifying the parameters of actuator model.
【作者单位】： 北京航空航天大学机械工程及自动化学院;
【分类号】：TH137
[Abstract]:Electric hydrostatic actuator has the advantages of high power density, high integration and high efficiency and energy saving. In order to obtain a more accurate linear mathematical model of actuator, genetic algorithm is used to identify the parameters of the model. In genetic algorithm, a set of model parameters is regarded as the gene coding of a chromosome, and the measured system frequency response data is taken as the criterion to evaluate the chromosomes, and the corresponding fitness function is constructed. The selection probability setting method based on sorting, arithmetic crossover operator and Gao Si mutation operator are used to carry out iterative operation to realize the genetic evolution operation of population and the search for the optimal solution. The final identification results demonstrate the effectiveness of genetic algorithm in identifying the parameters of actuator model.
【作者单位】： 北京航空航天大学机械工程及自动化学院;
【分类号】：TH137
【相似文献】
相关期刊论文 前10条
1 孔凡国;黄伟;;基于模糊理论和遗传算法融合的机械方案优选方法的研究[J];组合机床与自动化加工技术;2006年05期
2 侯Z诘，
本文编号：2275749
本文链接：https://www.wllwen.com/kejilunwen/jixiegongcheng/2275749.html
