基于遗传算法的双转子系统参数化建模

I. Darus, F. Aldebrez, M. Tokhi
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引用次数: 45

摘要

采用参数线性方法对悬停位置双转子多输入多输出系统(TRMS)进行了系统辨识。利用遗传算法(GA)优化技术对高度非线性系统的动态建模进行了研究,并与传统的递归最小二乘(RLS)技术进行了比较。利用遗传算法的全局搜索技术,在一步前预测的基础上识别出TRMS的参数。在时域和频域对两种模型在系统表征方面进行了比较评估。实验结果表明,遗传算法在线性参数化建模方面优于RLS算法。开发的遗传建模方法将用于未来工作中的控制设计和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parametric modelling of a twin rotor system using genetic algorithms
System identification using parametric linear approaches for modelling a twin rotor multi-input multi-output system (TRMS) in hovering position is presented in this work. The utilisation of a genetic algorithm (GA) optimisation technique for dynamic modelling of a highly non-linear system is studied in comparison to the conventional recursive least squares (RLS) technique. The global search technique of GA is used to identify the parameters of the TRMS based on one-step-ahead prediction. A comparative assessment of the two models in characterising the system is carried out in the time and frequency domains. Experimental results indicate the advantages of GA over RLS in linear parametric modelling. The developed genetic-modelling approach will be used for control design and development in future work.
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