This paper addresses the problem of recursive set-membership identification for linear time varying (LTV) systems when both input and output measurements are affected by bounded additive noise. First we formulate the problem of online computation of the parameter uncertainty intervals (PUIs) in terms of nonconvex polynomial optimization. Then, we propose a convex relaxation approach based on McCormick envelopes to solve the formulated problem to the global optimum by means of linear programming. The effectiveness of the proposed identification scheme is demonstrated by means of two simulation examples.

A convex optimization approach to online set-membership EIV identification of LTV systems / Fosson, Sophie M.; REGRUTO TOMALINO, Diego; Abdalla, TALAL ALMUTAZ ALMANSI; Salam, Abdul. - ELETTRONICO. - (2021), pp. 1442-1447. ((Intervento presentato al convegno The 2021 60th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) tenutosi a Tokyo (Japan) nel 8-10 Sept. 2021.

A convex optimization approach to online set-membership EIV identification of LTV systems

Sophie M. Fosson;Diego Regruto;Talal Abdalla;Abdul Salam
2021

Abstract

This paper addresses the problem of recursive set-membership identification for linear time varying (LTV) systems when both input and output measurements are affected by bounded additive noise. First we formulate the problem of online computation of the parameter uncertainty intervals (PUIs) in terms of nonconvex polynomial optimization. Then, we propose a convex relaxation approach based on McCormick envelopes to solve the formulated problem to the global optimum by means of linear programming. The effectiveness of the proposed identification scheme is demonstrated by means of two simulation examples.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2919392