: In this paper, two nonlinear optimization methods for the identification of nonlinear systems are compared. Both methods estimate all the parameters of a polynomial nonlinear sta...
Anne Van Mulders, Johan Schoukens, Marnix Volckaer...
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
— Control saturation is an important limitation in practical control systems and it is well known that performance degradation or instability may result if this limitation is not...
This paper addresses the state estimation problem of nonlinear systems. We formulate the problem using a minimum energy estimator (MEE) approach and propose an entropy penalized sc...
Sergio Daniel Pequito, A. Pedro Aguiar, Diogo A. G...
Ellipsoidal outer-bounding of the set of all feasible state vectors under model uncertainty is a natural extension of state estimation for deterministic models with unknown-but-bo...