This paper considers the state estimation problem of bilinear systems in the presence of
disturbances. The standard Kalman filter is recognized as the best state estimator for linear …

The identification of state-space models of bilinear systems is studied in this paper. The
parameters to be identified of the considered system are coupled with the unknown states …

This paper is concerned with the joint estimation of states and parameters of a special class
of nonlinear systems, ie, bilinear systems. The key is to investigate new estimation methods …

This paper derives the input‐output representation of the dynamical system described by a
linear multivariable state‐space model and the corresponding multivariate linear regressive …

This paper considers the identification problem of bilinear systems with measurement noise
in the form of the moving average model. In particular, we present an interactive estimation …

This paper investigates the recursive parameter and state estimation algorithms for a special
class of nonlinear systems (ie, bilinear state space systems). A state observer-based …

This paper proposes a novel iterative algorithm for the joint state and parameter estimation
of bilinear state–space systems disturbed by colored noise. Estimating the states and …

This study develops an adaptive filtering‐based recursive identification algorithm for joint
estimation of states and parameters of bilinear state‐space systems with an autoregressive …

This paper is concerned with the joint state and parameter estimation methods for a bilinear
system in the state space form, which is disturbed by additive noise. In order to overcome the …

In this paper, two methods for parameter estimation of bilinear state-space systems with
colored noise, which are expressed by ARMA model, are proposed. Using the hierarchical …