TY - EJOU
AU - Liu, Wentao
AU - Ma, Junxia
AU - Xiong, Weili
TI - State Estimation Moving Window Gradient Iterative Algorithm for Bilinear Systems Using the Continuous Mixed *p*-norm Technique
T2 - Computer Modeling in Engineering \& Sciences
PY - 2023
VL - 134
IS - 2
SN - 1526-1506
AB - This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space
models in the presence of disturbances. A bilinear state observer is designed for deriving identification algorithms
to estimate the state variables using the input-output data. Based on the bilinear state observer, a novel gradient
iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous
mixed *p*-norm cost function. The gain at each iterative step adapts to the data quality so that the algorithm has
good robustness to the noise disturbance. Furthermore, to improve the performance of the proposed algorithm, a
dynamic moving window is designed which can update the dynamical data by removing the oldest data and adding
the newest measurement data. A numerical example of identification of bilinear systems is presented to validate the
theoretical analysis.
KW - Bilinear state space model; parameter estimation; moving window; continuous mixed *p*-norm
DO - 10.32604/cmes.2022.020565