A recursive identification algorithm for linear discrete periodic systems

作     者：Lv, Lingling Zheng, Bingqian Zhang, Jinhua Zhang, Lei 

作者机构：Inst North China Univ Water Resources & Elect Pow Zhengzhou Henan Peoples R China Henan Univ Sch Comp & Informat Engn Inst Data & Knowledge Engn Kaifeng 475004 Henan Peoples R China 

出 版 物：《IET CONTROL THEORY AND APPLICATIONS》 (IET Control Theory Appl.)

年 卷 期：2023年第17卷第3期

页      面：331-340页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0804[工学-仪器科学与技术] 0811[工学-控制科学与工程] 

基　　金：National Key Research and Development Program of China [2019YFE0104800] Key Scientific Research Projects of Colleges and Universities in Henan Province [21A110005] Foundation of University Young Key Teacher of Henan Province [2020GGJS027] Team Project Funding of Scientic Research Innovation for Colleges and Universities in Henan Province [22IRTSTHN011] Science and Technology Research Project in Henan Province Excellent Youth Fund of Henan Natural Science Foundation 

主　　题：periodic control Simulation, modelling and identification time-invariant systems Time-varying control systems recursive identification algorithm Linear control systems linear discrete period time-varying systems parameter estimation two-step identification algorithm cyclic reconstruction method discrete systems Discrete control systems discrimination algorithm LDPV system parameter identification problem Interpolation and function approximation (numerical analysis) recursive least squares identification linear systems least squares approximations linear time-invariant system time-varying systems recursive principle-based identification algorithm recursive least squares principle 

摘      要：The parameter identification problem of linear discrete period time-varying (LDPV) systems is studied in this paper and a two-step identification algorithm based on the recursive least squares principle is proposed. The recursive principle-based identification algorithm is mostly used to deal with the parameter identification of time-invariant systems. Combine with the cyclic reconstruction method, the LDPV system is converted to a linear time-invariant system. Then, based on this and combined with recursive least squares identification, a discrimination algorithm is proposed for the parameter estimation of the LDPV system. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithm.