A Multiple Model Approach to Modeling Based on LPF Algorithm

CONTROL THEORY AND APPLICATION1. INTRODUCTIONMost complex industrial processes may be characterized as non-linear and non-stationary. The colltrol methodsbased on linear models have then been challenged. Modeling and control of complex nonlinear systems becomesone of the difficult problems, which persecute control theory research and application. Several methods havebeen developed for known-structure system identification, including NARMAX, Hammerstein, Wiener or alsoHammers…

A Multiple Model Approach to Modeling Based on LPF Algorithm

Input-output data fitting methods are often used for unknown-structure nonlinear system modeling. Based on model-on-demand tactics, a multiple model approach to modeling for nonlinear systems is presented. The basic idea is to find out, from vast historical system input-output data sets, some data sets matching with the current working point, then to develop a local model using Local Polynomial Fitting (LPF) algorithm. With the change of working points, multiple local models are built, which realize the exact modeling for the global system. By comparing to other methods, the simulation results show good performance for its simple, effective and reliable estimation.