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In the paper a fast computational routines for identification algorithms for recovering nonlinearities in Hammerstein systems based on orthogonal series expansions of functions are proposed. It is ascertained that both, convergence conditions and convergence rates of the computational algorithms are the same as their much less computationaly attractive ’theoretic’ counterparts. The generic computational algorithm is derived and illustrated by three examples based on standard orthogonal series on interval, viz. Fourier, Legendre, and Haar systems. The exemplary algorithms are presented in a detailed, ready-to-implement, form and examined by means of computer simulations.

COMPUTATIONAL ALGORITHM FOR NONPARAMETRIC MODELLING OF NONLINEARITIES IN HAMMERSTEIN SYSTEMS