废气氧传感器Hammerstein模型结构的确定

研究了废气氧(EGO)传感器Hammerstein模型结构辨识方法。静态非线性函数选用双曲正切与多项式组合形式,动态线性环节分别选用带外生变量的自回归(ARX)模型、输出误差(OE)模型和Box-Jenkins(BJ)模型结构。采用交叉准则法进行参数估计和阶次选择,通过仿真比较对模型进行检验。结果表明:最终输出误差(FOE)准则和最终预报误差(FPE)准则均适用于用估计数据选择阶次,但前者比后者更可靠。基于预测误差法的3阶OE模型和BJ模型均可用于EGO传感器Hammerstein模型动态线性环节的建模。

Determinating Hammerstein model structure of exhaust gas oxygen sensor

The Hammerstein model structure identification method of an exhaust gas oxygen(EGO) sensor is studied.Combination of hyperbolic tangent with polynomial is selected as static non-linear function,and linear dynamic part of the model is chosen respectively as auto-regression with exogenous variable(ARX) model,output error(OE) model and Box-Jenkins(BJ) model.The cross-criterion method is used for parameter estimation and orders selection,and the models are checked by simulation comparison.Results show that final output error(FOE) criterion and final prediction error(FPE) criterion are suitable for choosing order with estimation data,while the former is more reliable than the latter.Both OE model and BJ model with three orders based on prediction error method can be used for modeling linear dynamic part of the Hammerstein model for EGO sensor.