Fuzzy supervisor for neural emulation of MIMO nonlinear processes

This paper present a fuzzy supervisor for neural emulator of nonlinear MIMO processes to guarantee good performances of the neural emulator by its convergence rapidity and its accurent representation. In this proposed case, without initializing the parameter and online adaptation, both are needed. Numerical simulations are realized to clarify the performances improvement relatively to the classical case where the starting term is necessary.