Gradient-Based Recursive Identification Methods for Input Nonlinear Equation Error Closed-Loop Systems

被引：0
作者：
Bingbing Shen
Feng Ding
Ahmed Alsaedi
Tasawar Hayat
机构：
[1] Jiangnan University,Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering
[2] King Abdulaziz University,Department of Mathematics, Nonlinear Analysis and Applied Mathematics (NAAM) Research Group
[3] Quaid-I-Azam University,Department of Mathematics
来源：
Circuits, Systems, and Signal Processing | 2017年 / 36卷
关键词：
Parameter estimation; Stochastic gradient; Multi-innovation; Hierarchical identification; Nonlinear system; Closed-loop system;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The identification problem of closed-loop or feedback nonlinear systems is a hot topic. Based on the hierarchical identification principle, this paper presents a hierarchical stochastic gradient algorithm and a hierarchical multi-innovation stochastic gradient algorithm for feedback nonlinear systems. The simulation results show that the hierarchical multi-innovation stochastic gradient can more effectively estimate the parameters of the feedback nonlinear systems than the hierarchical stochastic gradient algorithm.
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收藏
页码：2166 / 2183
页数：17
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共 109 条
[1]  
Bai EW(1998)An optimal two-stage identification algorithm for Hammerstein–Wiener nonlinear systems Automatica 34 333-338
[2]  
Bai E(2012)How nonlinear parametric Wiener system identification is under Gaussian inputs? IEEE Trans. Automat. Control 57 738-742
[3]  
Cai Z(2016)Multi-AUV target search based on bioinspired neurodynamics model in 3-D underwater environments IEEE Trans. Neural Netw. Learn. Syst. 353 398-408
[4]  
Cao X(2016)Observer-based adaptive neural network trajectory tracking control for remotely operated Vehicle IEEE Trans. Neural Netw. Learn. Syst. 353 1518-1526
[5]  
Zhu DQ(2016)An auxiliary model based least squares algorithm for a dual-rate state space system with time-delay using the data filtering J. Franklin Inst. 301 135-143
[6]  
Yang SX(2016)The recursive least squares identification algorithm for a class of Wiener nonlinear systems J. Franklin Inst. 35 3323-3338
[7]  
Chu ZZ(2016)Kalman state filtering based least squares iterative parameter estimation for observer canonical state space systems using decomposition J. Comput. Appl. Math. 13 237-241
[8]  
Zhu DQ(2016)Recursive least squares parameter estimation for a class of output nonlinear systems based on the model decomposition Circuits Syst. Signal Process. 73 583-592
[9]  
Yang SX(2016)Array factor forming for image reconstruction of one-dimensional nonuniform aperture synthesis radiometers IEEE Geosci. Remote Sens. Lett. 34 1499-1517
[10]  
Ding F(2013)Multistage least squares based iterative estimation for feedback nonlinear systems with moving average noises using the hierarchical identification principle Nonlinear Dyn. 35 154-168
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