A new model order identification algorithm with application to automobile oxygen sensor modeling

A method of determining the model order of MIMO nonlinear dynamic systems was proposed using the concept of the coherence function. It was demonstrated that the proposed scheme is extremely successful even in the presence of noise, clearly outperforms the Lipschitz criterion scheme in determining the model order accurately and unambiguously and identifies the order correctly even in the case when the Lipschitz scheme produces an erroneous result. The effectiveness of the order determination scheme in conjunction with the NARMAX identification technique, for identifying a severely nonlinear system such as an automobile exhaust gas oxygen (EGO) sensor was also studied. It was shown that the proposed scheme is suitable for practical implementation using simulation results