Combined state and least squares parameter estimation algorithms for dynamic systems

被引：216
|
作者：
Ding, Feng [1 ,2 ]
机构：
[1] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China
[2] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
来源：
APPLIED MATHEMATICAL MODELLING | 2014年 / 38卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Dynamic system; Numerical algorithm; Least squares; Parameter estimation; Recursive identification; State space model; IDENTIFICATION METHODS; ITERATIVE ESTIMATION; PERFORMANCE ANALYSIS; MODEL;
D O I：
10.1016/j.apm.2013.06.007
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The control theory and automation technology cast the glory of our era. Highly integrated computer chip and automation products are changing our lives. Mathematical models and parameter estimation are basic for automatic control. This paper discusses the parameter estimation algorithm of establishing the mathematical models for dynamic systems and presents an estimated states based recursive least squares algorithm, and the states of the system are computed through the Kalman filter using the estimated parameters. A numerical example is provided to confirm the effectiveness of the proposed algorithm. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码：403 / 412
页数：10
相关论文
共 50 条
  • [1] Recursive and iterative least squares parameter estimation algorithms for observability canonical state space systems
    Ma, Xingyun
    Ding, Feng
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2015, 352 (01): : 248 - 258
  • [2] Least Squares Estimation and Kalman Filter Based Dynamic State and Parameter Estimation
    Fan, Lingling
    [J]. 2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2015,
  • [3] Dynamic least squares parameter estimation of structures
    Yap, KC
    Zimmerman, DC
    [J]. IMAC-XVIII: A CONFERENCE ON STRUCTURAL DYNAMICS, VOLS 1 AND 2, PROCEEDINGS, 2000, 4062 : 1513 - 1519
  • [4] Separable Nonlinear Least-Squares Parameter Estimation for Complex Dynamic Systems
    Dattner, Itai
    Ship, Harold
    Voit, Eberhard O.
    [J]. COMPLEXITY, 2020, 2020
  • [5] Filtering based least squares parameter estimation algorithms for Hammerstein nonlinear CARMA systems
    Mao, Yawen
    Ding, Feng
    Pan, Jian
    Ding, Wenfang
    Wan, Xiangkui
    [J]. 2017 AMERICAN CONTROL CONFERENCE (ACC), 2017, : 574 - 579
  • [6] LEAST-SQUARES PARAMETER-ESTIMATION ALGORITHMS FOR NON-LINEAR SYSTEMS
    BILLINGS, SA
    VOON, WSF
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1984, 15 (06) : 601 - 615
  • [7] Efficient Total Least Squares State and Parameter Estimation for Differentially Flat Systems
    Liu, Ji
    Mendoza, Sergio
    Li, Guang
    Fathy, Hosam
    [J]. 2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 5419 - 5424
  • [8] COMPARISON OF 2 ALGORITHMS FOR LEAST-SQUARES PARAMETER ESTIMATION
    LUECKE, RH
    BRITT, HI
    HALL, KR
    [J]. CRYOGENICS, 1974, 14 (05) : 284 - 284
  • [9] ORTHOGONAL LEAST-SQUARES PARAMETER-ESTIMATION ALGORITHMS FOR NONLINEAR STOCHASTIC-SYSTEMS
    BILLINGS, SA
    JONES, GN
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1992, 23 (07) : 1019 - 1032
  • [10] STATE ESTIMATION IN DISTRIBUTED PARAMETER SYSTEMS VIA LEAST-SQUARES AND INVARIANT EMBEDDING
    LAMONT, GB
    KUMAR, KSP
    [J]. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 1972, 38 (03) : 588 - &
12345