Parameter identification of fractional order system using enhanced response sensitivity approach

作     者：Liu, G. Wang, L. Luo, W. L. Liu, J. K. Lu, Z. R. 

作者机构：Sun Yat Sen Univ Sch Aeronaut & Astronaut Dept Appl Mech & Engn 135 Xingang Rd Guangzhou 510275 Guangdong Peoples R China Guangzhou Univ Sch Civil Engn 230 Wai Huan West Rd Guangzhou 510006 Guangdong Peoples R China 

出 版 物：《COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION》 (非线性科学和数值模拟快报)

年 卷 期：2019年第67卷第Feb.期

页      面：492-505页

核心收录：

学科分类：07[理学] 0701[理学-数学] 0702[理学-物理学] 0801[工学-力学（可授工学、理学学位）] 070101[理学-基础数学] 

基　　金：National Natural Science Foundation of China Natural Science Foundation of Guangdong Province [2015A030313126] Science and Technology Planning Project of Guangdong Province [2016A020223006] Fundamental Research Funds for the Central Universities [17lgjc42] 

主　　题：Fractional order system Computational scheme Parameter identification Enhanced response sensitivity approach 

摘      要：This paper presents an investigation on parameters identification of fractional order system based on the enhanced response sensitivity approach. Compared with the integer order differential operator, fractional order operator can describe the characteristics of some phenomena more accurately such as hereditary and memory properties. In order to achieve the solution of the fractional order system, a new computational scheme is presented in this paper based on Adams-type scheme and the Newmark -beta method. Such an identification problem is classed as an inverse problem and can be modeled as an nonlinear optimization problem. In this paper, the enhanced response sensitivity approach is derived and used to identify the parameters of the fractional order system. To this end, the time domain response of the fractional order system is obtained by the proposed computational scheme, then the response sensitivity with respect to the parameter is achieved as well. Numerical examples illustrated the computing and identification procedure and shown the accuracy and the convergence of identification scheme. (C) 2018 Elsevier B.V. All rights reserved.