Bayesian system identification and chaotic prediction from data for stochastic Mathieu-van der Pol-Duffing energy harvester

作     者：Di Liu Shen Xu Jinzhong Ma Di Liu;Shen Xu;Jinzhong Ma

作者机构：School of Mathematics SciencesShanxi University030006TaiyuanShanxiChina 

出 版 物：《Theoretical & Applied Mechanics Letters》 (力学快报（英文版）)

年 卷 期：2023年第13卷第2期

页      面：89-92页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work is supported by the National Nature Science Founda-tion of China(Nos.11972019 and 12102237) 

主　　题：Vibration energy harvester Approximate Bayesian computation 0–1 test Parameter identification Chaotic prediction 

摘      要：In this paper,the approximate Bayesian computation combines the particle swarm optimization and se-quential Monte Carlo methods,which identify the parameters of the Mathieu-van der Pol-Duffing chaotic energy harvester *** the proposed method is applied to estimate the coefficients of the chaotic model and the response output paths of the identified coefficients compared with the observed,which verifies the effectiveness of the proposed ***,a partial response sample of the regular and chaotic responses,determined by the maximum Lyapunov exponent,is applied to detect whether chaotic motion occurs in them by a 0-1 *** paper can provide a reference for data-based parameter iden-tification and chaotic prediction of chaotic vibration energy harvester systems.