State Estimation Moving Window Gradient Iterative Algorithm for Bilinear Systems Using the Continuous Mixed p-norm Technique  

作　　者：Wentao Liu Junxia Ma Weili Xiong 

机构地区：[1]Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),School of Internet of Things Engineering,Jiangnan University,Wuxi,214122,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第2期873-892,共20页工程与科学中的计算机建模（英文）

基　　金：funded by the National Natural Science Foundation of China(No.61773182);the 111 Project(B12018).

摘　　要：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 dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.

关 键 词：Bilinear state space model parameter estimation moving window continuous mixed p-norm 

分 类 号：TP38[自动化与计算机技术—计算机系统结构]