Identification of fractional order Hammerstein models based on mixed signals
作者机构：School of Control Science and EngineeringDalian University of TechnologyDalianPeople’s Republic of China School of Electrical EngineeringXinjiang UniversityUrumqiPeople’s Republic of China
出 版 物：《Journal of Control and Decision》 (控制与决策学报（英文）)
年 卷 期：2024年第11卷第1期
页 面：132-138页
核心收录：
学科分类：0808[工学-电气工程] 07[理学] 0811[工学-控制科学与工程] 0701[理学-数学] 070101[理学-基础数学]
基 金：National Natural Science Foundation of China[grant number 61863034]
主 题：Mixed signal fractional order Hammerstein model neural fuzzy network model multi-innovation Levenberg-Marquardt algorithm
摘 要：An algorithm based on mixed signals is proposed,to solve the issues of low accuracy of identification algorithm,immeasurable intermediate variables of fractional order Hammerstein model,and how to determine the magnitude of fractional *** this paper,a special mixed input signal is designed to separate the nonlinear and linear parts of the fractional order Hammerstein model so that each part can be identified *** nonlinear part is fitted by the neural fuzzy network model,which avoids the limitation of polynomial fitting and broadens the application range of nonlinear *** addition,the multi-innovation Levenberg-Marquardt(MILM)algorithm and auxiliary recursive least square algorithm are innovatively integrated into the parameter identification algorithm of the fractional order Hammerstein model to obtain more accurate identification results.A simulation example is given to verify the accuracy and effectiveness of the proposed method.
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