In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman f...

the problem of observer design for nonlinear systems has got great attention in the recent literature. the nonlinear observer has been a topic of interest in control theory. in this research, a modified robust sliding-mode observer (smo) is designed to accurately estimate the state variables of nonlinear systems in the presence of disturbances and model uncertainties. the observer has a simple ...

In this paper a novel method based on evolutionary algorithms is presented to estimate the harmonic components. In general, the optimization of the harmonic estimation process is a multi-component problem, in which evaluation of the phase and harmonic frequency is the nonlinear part of the problem and is solved based on the mathematical and evolutionary methods; while estimation of amplitude of...

great effect of three way catalytic convertor (twc) performance on oxygen sensor output voltage has made the sensor (located after catalyst) as the main signal in almost all today’s twc monitoring algorithms. in this paper output voltage of nonlinear oxygen sensor is estimated using a nonlinear autoregressive with exogenous inputs (narx) model. the estimation uses ecu calculated exhaust gas flo...

In this paper we discuss about nonlinear pseudoparabolic equations with nonlocal boundary conditions and their results. An effective error estimation for this method altough has not yet been discussed. The aim of this paper is to fill this gap.

Many systems in the real world are more accurately described by nonlinear models. Since the original work of Kalman (Kalman, 1960; Kalman & Busy, 1961), which introduces the Kalman filter for linear models, extensive research has been going on state estimation of nonlinear models; but there do not yet exist any optimum estimation approaches for all nonlinear models, except for certain classes o...

This chapter deals with the description, the parametric estimation, the state estimation, and the parametric and state estimation conjointly of nonlinear systems. The focus is on the class of nonlinear systems, which are described by Wiener state-space discrete-time mathematical models. Thus, the authors develop a new recursive parametric estimation algorithm, which is based on least squares te...

This paper is a survey of SAS System features for nonlinear models, with emphasis on new features for nonlinear regression. Topics include automatic calculation of analytic derivatives, estimation with nonlinear parameter restrictions, tests of nonlinear hypotheses, maximum likelihood and generalized method of moments (GMM) estimation, estimation of simultaneous systems of nonlinear regression ...