A receding horizon Kalman finite-impulse response (FIR) filter is suggested for continuous-time systems, combining the Kalman filter with the receding horizon strategy. In the suggested filter, the horizon initial state is assumed to be unknown. It can always be obtained irrespective of unknown information on the horizon initial state, The filter may be the first stochastic FIR form for continuous-time systems that may have many good inherent properties. The suggested filter can be represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer. The validity of the suggested filter is illustrated by numerical examples.X1144sciescopu
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...
Abstract: A receding horizon filtering problem for nonlinear continuous-time stochastic systems is ...
The paper presents a state predictor for linear time-varying systems using Kalman filter with the re...
In this study, the authors consider the receding horizon filtering problem for discrete-time linear ...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
Finite impulse response (FIR) state estimation algorithms have been much discussed in literature lat...
This paper describes a new design for a recursive least-squares (RLS) and finite impulse response (F...
This paper addresses a new design method of recursive least-squares (RLS) and finite impulse respons...
This paper is concerned with the filtering problem in continuous time. Three algorithmic solution ap...
This paper is concerned with the filtering problem in continuous time. Three algorithmic solution ap...
This paper addresses a new design method of recursive least-squares (RLS) and finite impulse respons...
This paper examines two classes of algorithms that estimate a continuous time ARX type of models fro...
In this paper, a robust finite-horizon Kalman filter is designed for discrete time-varying uncertain...
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...
Abstract: A receding horizon filtering problem for nonlinear continuous-time stochastic systems is ...
The paper presents a state predictor for linear time-varying systems using Kalman filter with the re...
In this study, the authors consider the receding horizon filtering problem for discrete-time linear ...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
Finite impulse response (FIR) state estimation algorithms have been much discussed in literature lat...
This paper describes a new design for a recursive least-squares (RLS) and finite impulse response (F...
This paper addresses a new design method of recursive least-squares (RLS) and finite impulse respons...
This paper is concerned with the filtering problem in continuous time. Three algorithmic solution ap...
This paper is concerned with the filtering problem in continuous time. Three algorithmic solution ap...
This paper addresses a new design method of recursive least-squares (RLS) and finite impulse respons...
This paper examines two classes of algorithms that estimate a continuous time ARX type of models fro...
In this paper, a robust finite-horizon Kalman filter is designed for discrete time-varying uncertain...
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...