公开(公告)号：US20100023464A1

公开(公告)日：2010-01-28

申请号：US12220446

申请日：2008-07-24

申请人： Kourosh Danai ,  James McCusker

发明人： Kourosh Danai ,  James McCusker

IPC分类号： G06F15/18 ,  G06F17/00 ,  G06F17/20

CPC分类号： G05B17/02

摘要： A method of parameter adaptation is used to modify the parameters of a model to improve model performance. The model separately estimates the contribution of each model parameter to the prediction error. It achieves this by transforming to the time-scale plane the vectors of output sensitivities with respect to model parameters and then identifying the regions within the time-scale plane at which the dynamic effect of individual model parameters is dominant on the output. The method then attributes the prediction error in these regions to the deviation of a single parameter from its true value as the basis of estimating individual parametric errors. The proposed Signature Isolation Method (PARSIM) then uses these estimates to adapt individual model parameters independently of the others, implementing, in effect, concurrent adaptation of individual parameters by the Newton-Raphson method in the time-scale plane. The Signature Isolation Method has been found to have an adaptation precision comparable to that of the Gauss-Newton method for noise-free cases. However, it surpasses the Gauss-Newton method in precision when the output is contaminated with noise or when the measurements are generated by inadequate excitation.

摘要翻译： 参数调整方法用于修改模型的参数以提高模型性能。 该模型分别估计每个模型参数对预测误差的贡献。 通过将时间尺度平面转换为模型参数的输出灵敏​​度矢量，然后识别时间尺度平面内的各个模型参数的动态效应在输出上占优势的区域来实现。 然后，该方法将这些区域中的预测误差归因于单个参数与其真实值的偏差，作为估计各个参数误差的基础。 所提出的签名隔离方法（PARSIM）然后使用这些估计来独立于其他模型参数来适应各自的模型参数，实际上通过在时间尺度平面中的牛顿 - 拉夫逊方法实现各个参数的并发适应。 已经发现签名隔离方法具有与用于无噪声情况的高斯 - 牛顿法相当的适应精度。 然而，当输出被噪声污染或当激励不足产生测量时，它的精度超过了高斯 - 牛顿法。

公开(公告)号：US20110167025A1

公开(公告)日：2011-07-07

申请号：US12902687

申请日：2010-10-12

申请人： Kourosh Danai ,  James R. McCusker

发明人： Kourosh Danai ,  James R. McCusker

IPC分类号： G06F15/18 ,  G06N5/02

CPC分类号： G05B17/02

摘要： A method of parameter adaptation is used to modify the parameters of a model to improve model performance. The model separately estimates the contribution of each model parameter to the prediction error. It achieves this by transforming to the time-scale plane the vectors of output sensitivities with respect to model parameters and then identifying the regions within the time-scale plane at which the dynamic effect of individual model parameters is dominant on the output. The method then attributes the prediction error in these regions to the deviation of a single parameter from its true value as the basis of estimating individual parametric errors. The proposed Signature Isolation Method (PARSIM) then uses these estimates to adapt individual model parameters independently of the others, implementing, in effect, concurrent adaptation of individual parameters by the Newton-Raphson method in the time-scale plane. The Signature Isolation Method has been found to have an adaptation precision comparable to that of the Gauss-Newton method for noise-free cases. However, it surpasses the Gauss-Newton method in precision when the output is contaminated with noise or when the measurements are generated by inadequate excitation.

摘要翻译： 参数调整方法用于修改模型的参数以提高模型性能。 该模型分别估计每个模型参数对预测误差的贡献。 通过将时间尺度平面转换为模型参数的输出灵敏​​度矢量，然后识别时间尺度平面内的各个模型参数的动态效应在输出上占优势的区域来实现。 然后，该方法将这些区域中的预测误差归因于单个参数与其真实值的偏差，作为估计各个参数误差的基础。 所提出的签名隔离方法（PARSIM）然后使用这些估计来独立于其他模型参数来适应各自的模型参数，实际上通过在时间尺度平面中的牛顿 - 拉夫逊方法实现各个参数的并发适应。 已经发现签名隔离方法具有与用于无噪声情况的高斯 - 牛顿法相当的适应精度。 然而，当输出被噪声污染或当激励不足产生测量时，它的精度超过了高斯 - 牛顿法。

公开(公告)号：US08712927B2

公开(公告)日：2014-04-29

申请号：US12220446

申请日：2008-07-24

申请人： Kourosh Danai ,  James McCusker

发明人： Kourosh Danai ,  James McCusker

IPC分类号： G06F15/18

CPC分类号： G05B17/02

摘要： A method of parameter adaptation is used to modify the parameters of a model to improve model performance. The model separately estimates the contribution of each model parameter to the prediction error. It achieves this by transforming to the time-scale plane the vectors of output sensitivities with respect to model parameters and then identifying the regions within the time-scale plane at which the dynamic effect of individual model parameters is dominant on the output. The method then attributes the prediction error in these regions to the deviation of a single parameter from its true value as the basis of estimating individual parametric errors. The proposed Parameter Signature Isolation Method (PARSIM) then uses these estimates to adapt individual model parameters independently of the others, implementing, in effect, concurrent adaptation of individual parameters by the Newton-Raphson method in the time-scale plane.

摘要翻译： 参数调整方法用于修改模型的参数以提高模型性能。 该模型分别估计每个模型参数对预测误差的贡献。 通过将时间尺度平面转换为模型参数的输出灵敏​​度矢量，然后识别时间尺度平面内的各个模型参数的动态效应在输出上占优势的区域来实现。 然后，该方法将这些区域中的预测误差归因于单个参数与其真实值的偏差，作为估计各个参数误差的基础。 所提出的参数签名隔离方法（PARSIM）然后使用这些估计来独立于其他模型参数来适应各自的模型参数，实际上通过在时间尺度平面中的牛顿 - 拉夫逊方法实现各个参数的并发适应。