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Matching of linear dynamic model of process based on known frequency characteristic using a non-quadratic measure of model error

机译:基于已知频率特性的基于模型误差的非二次测量的基于已知频率特性的线性动态模型匹配

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The paper presents a new approach to derivation of a linear model representing an approximation of dynamic response determined for a model estimated within discrete time identification. The approximation is calculated using with new algorithm, that minimize the approximation error with application a non-quadratic performance index. The used performance index is quite close to the absolute norm of error, but has better convergence features. The recursive formula for derivation of the approximation model coefficients is derived and tested on two different examples of two dynamic processes.
机译:本文提出了一种推导出线性模型的新方法,表示针对在离散时间识别内估计的模型确定的动态响应的近似。近似使用新算法计算,可最大限度地提高应用程序非二次性能索引的近似误差。使用的性能索引非常接近于绝对的错误规范,但具有更好的收敛功能。导出用于达到近似模型系数的递归公式,并在两个动态过程的两个不同示例上进行测试。

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