%P 2819-2824
%T Set-membership identification of Hammerstein-Wiener systems
%O 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), held in Orlando USA), December 12-15, 2011
%I IEEE
%A Vito Cerone
%A Dario Piga
%A Diego Regruto
%K Decision support systems; Noise; Optimization; Polynomials; Uncertain systems; Uncertainty; Vector
%X Set-membership identification of Hammerstein-Wiener models is addressed in the paper. First, it is shown that computation of tight parameter bounds requires the solutions to a number of nonconvex constrained polynomial optimization problems where the number of decision variables increases with the length of the experimental data sequence. Then, a suitable convex relaxation procedure is presented to significantly reduce the computational burden of the identification problem. A detailed discussion of the identification algorithm properties is reported. Finally, a simulated example is used to show the effectiveness and the computational tractability of the proposed approach.
%D 2011
%L eprints2445
%B Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC)
%R 10.1109/CDC.2011.6161172