Wentao Liu, Junxia Ma, Weili Xiong*
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 873-892, 2023, DOI:10.32604/cmes.2022.020565
Abstract 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… More >
Login
Register
