Relative gain array of weakly nonlinear systems using a nonparametric identification approach
الباحث الأول:
Ali MH Kadhim,
الباحثين الآخرين:
Miguel Castano, Wolfgang Birk, Thomas Gustafsson
المجلة:
Control Applications (CCA), 2015 IEEE Conference
تاريخ النشر:
None
مختصر البحث:
This article presents a procedure to estimate the relative gain array (RGA) matrix for weakly nonlinear systems by means of nonparametric identification of the frequency response matrix (FRM). Specifically, the best linear approximation of nonlinear…
This article presents a procedure to estimate the relative gain array (RGA) matrix for weakly nonlinear systems by means of nonparametric identification of the frequency response matrix (FRM). Specifically, the best linear approximation of nonlinear systems and the covariance of the nonlinear distortions are used in the relative gain array estimation. For the estimation neither process model nor model structure need to be known which is an advantage over methods that require accurate knowledge of a parametric process model. The proposed approach is compared with the original RGA and a nonlinear RGA calculation using the well-known quadruple tank process as a case.
