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 …

Parameter estimation is important in signal modeling and signal filtering. This paper uses
the filtering technique to study the parameter estimation problems of a class of bilinear …

This study presents a combined parameter and state estimation algorithm for a bilinear
system described by its observer canonical state‐space model based on the hierarchical …

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 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 considers the iterative parameter estimation for a dual‐rate sampled‐data
bilinear system with autoregressive moving average noise. Through combining the auxiliary …

Although some dynamic behaviors are commonly modeled as the linear or bilinear systems,
recent studies have consistently noted the existence of significant nonlinearities in these …

This paper considers the parameter identification problem of bilinear systems, which are a
special class of nonlinear systems. The basic idea is giving the input–output representation …

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 …