Separable Synchronous Gradient‐Based Iterative Algorithms for the Nonlinear ExpARX System

Author:

Gu Ya1ORCID,Hou Yuting1,Li Chuanjiang1ORCID,Zhu Yanfei1

Affiliation:

1. College of Information Mechanical and Electrical Engineering, Shanghai Normal University Shanghai People's Republic of China

Abstract

ABSTRACTThis article is aimed to study the parameter identification of the ExpARX system. To overcome the computational complexity associated with a large number of feature parameters, a parameter separation scheme based on the different features of the identification model is introduced. In terms of the phenomenon that the coupling parameters lead to the inability of algorithms, a separable synchronous interactive estimation method is introduced to eliminate the coupling parameters and perform parameter estimation in accordance with the hierarchical principle. For the purpose of achieving high‐accuracy performance and reducing complexity, a separable synchronous gradient iterative algorithm is derived by means of gradient search. In order to improve the identification accuracy, a separable synchronous multi‐innovation gradient iterative algorithm is proposed by introducing the multi‐innovation identification theory. In order to improve the convergence speed, a separable synchronous multi‐innovation conjugate gradient iterative algorithm is proposed by introducing the conjugate gradient theory. Finally, a simulation example and a real‐life example of piezoelectric ceramics are used to verify the effectiveness of the proposed algorithm.

Funder

Natural Science Foundation of Shanghai Municipality

National Natural Science Foundation of China

Publisher

Wiley

Reference148 articles.

1. Identification and U‐Control of a State‐Space System With Time‐Delay;Gu Y.;International Journal of Adaptive Control and Signal Processing,2022

2. An Identification Algorithm of Generalized Time‐Varying Systems Based on the Taylor Series Expansion and Applied to a pH Process;Ji Y.;Journal of Process Control,2023

3. Least Squares Parameter Estimation and Multi‐Innovation Least Squares Methods for Linear Fitting Problems From Noisy Data;Ding F.;Journal of Computational and Applied Mathematics,2023

4. Hierarchical Multi‐Innovation Stochastic Gradient Identification Algorithm for Estimating a Bilinear State‐Space Model With Moving Average Noise;Gu Y.;Journal of Computational and Applied Mathematics,2023

5. Filtering‐Based Accelerated Estimation Approach for Generalized Time‐Varying Systems With Disturbances and Colored Noises;Ji Y.;IEEE Transactions on Circuits and Systems II: Express Briefs,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3