MIMO linear systems identification in the presence of bounded noise

In this paper we consider the problem of set-membership identification of multiple-inputs multiple-outputs (MIMO) linear models when both input and output measurements are affected by bounded additive noise. First a general formulation is proposed which allows the user to take into account possible a-priori information about the structure of the MIMO model to be identified. Then, the problem is formulated in terms of a suitable polynomial optimization problem, which is solved by means of a convex relaxation approach. A simulation example is presented in order to show the effectiveness of the proposed approach.