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Model reduction using the genetic algorithm and routh approximations

机译:使用遗传算法和Routh逼近进行模型约简

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摘要

A new method of model reduction combining the genetic algorithm(GA) with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time delay. The denominator parameters of the reduced-order model are determined by the Routh approximation method, then the numerator parameters and time delay are identified by the GA. The reduced-order models obtained by the proposed method will always be stable if the original system is stable and produce a good approximation to the original system in both the frequency domain and time domain. Two numerical examples show that the method is computationally simple and efficient.
机译:提出了一种将遗传算法与劳斯逼近相结合的模型约简新方法。建议可以通过具有时滞的低阶模型来近似高阶系统。降阶模型的分母参数由劳斯近似法确定,分子参数和时延由遗传算法确定。如果原始系统是稳定的,则通过所提方法获得的降阶模型将始终保持稳定,并且在频域和时域上均能很好地逼近原始系统。两个数值例子表明,该方法在计算上简单高效。

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