Filter identification with fuzzy logic transition

The chapter gives the fuzzy filter description considering the filter operational principles and fuzzy logic basic properties. The digital filter has the objective that the output filter signal converges to output model signal, obtaining the best answer correspondence, having the minimum filter error in the mean square criterion sense. A fuzzy mechanism is added to filter transition structure, transforming in an intelligent filter, selecting and emitting a decision answer according to real output process changes. The fuzzy logic estimation actualizes the parametres and internal filter gain, converging to the real dynamical process answer. In estimation form, the input signal filter is analyzed into levels operations updating the filter weights giving the approximation answers in accordance with the reference signal in natural form. Finally, the chapter shows fuzzy filter simulation results using the Kalman structure applied in Matlab tools.