Open AccessRobust stability of moving horizon estimation for non‐linear systems with bounded disturbances using adaptive arrival cost
Author(s) -
Deniz Nestor,
Murillo Marina,
Sanchez Guido,
Giovanini Leonardo
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0523
Subject(s) - estimator , control theory (sociology) , convergence (economics) , bounded function , stability (learning theory) , exponential stability , mathematics , linear system , state (computer science) , horizon , mathematical optimization , adaptive estimator , computer science , nonlinear system , algorithm , statistics , control (management) , artificial intelligence , mathematical analysis , geometry , machine learning , physics , quantum mechanics , economics , economic growth
The robust stability and convergence to the true state of a moving horizon estimator based on an adaptive arrival cost are established for non‐linear detectable systems in this study. Robust global asymptotic stability is shown for the case of non‐vanishing bounded disturbances, whereas the convergence to the true state is proved for the case of vanishing disturbances. Two simulations were made to show the estimator behaviour under different operational conditions and to compare it with the state of the art of estimation methods.