AbstractThis article addresses the parametric identification of block‐structured nonlinear systems in a general form, characterized by the feedback interconnection of a multivariable linear system and a static multivariate nonlinear map. We assume that both the input and the output collected data are affected by bounded noise, which casts the problem in the context of set‐membership (SM) errors‐in‐variables identification. We introduce a single‐stage SM identification algorithm for the computation of the parameter uncertainty intervals. The proposed solution exploits the formulation of a suitable optimization problem solved through convex relaxation techniques. Numerical simulations and an experimental test show the effectiveness of the proposed approach.