%X In this paper, we consider the set-membership error-in-variables identification problem, that is the identification of linear dynamic systems when output and input measurements are corrupted by bounded noise. A new approach for the computation of parameters uncertainty intervals is presented. First, the problem is formulated in terms of nonconvex optimization. Then, a relaxation procedure is proposed to compute parameter bounds by means of semidefinite programming techniques. Finally, accuracy of the estimate and computational complexity of the proposed algorithm are discussed. Advantages of the proposed technique with respect to previously published ones are discussed both theoretically and by means of a simulated example
%L eprints2464
%D 2010
%A Vito Cerone
%A Dario Piga
%A Diego Regruto
%J International Journal of Adaptive Control and Signal Processing
%R doi:10.1002/acs.1218
%N 3
%T Improved parameter bounds for set-membership EIV problems
%P 208-227
%V 25
%I Wiley
%O Special Issue: Bounding Methods for State and Parameter Estimation