Parameter estimation for control systems based on impulse responses

被引:15
作者
Xu, Ling [1 ,2 ]
Ding, Feng [2 ]
机构
[1] Wuxi Vocat Inst Commerce, Sch Internet Things Technol, Wuxi 214153, Peoples R China
[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China
基金
中国国家自然科学基金;
关键词
Gradient method; iterative method; nonlinear optimization; parameter estimation; RELAY FEEDBACK TEST; TIME-DELAY SYSTEMS; ESTIMATION ALGORITHMS; IDENTIFICATION METHOD; DYNAMICAL-SYSTEMS; NEWTON ITERATION; LINEAR-SYSTEMS; STEP RESPONSES; STATE; MODEL;
D O I
10.1007/s12555-016-0224-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The impulse signal is an instant change signal in very short time. It is widely used in signal processing, electronic technique, communication and system identification. This paper considers the parameter estimation problems for dynamical systems by means of the impulse response measurement data. Since the cost function is highly nonlinear, the nonlinear optimization methods are adopted to derive the parameter estimation algorithms to enhance the estimation accuracy. By using the iterative scheme, the Newton iterative algorithm and the gradient iterative algorithm are proposed for estimating the parameters of dynamical systems. Also, a damping factor is introduced to improve the algorithm stability. Finally, using simulation examples, this paper analyzes and compares the merit and weakness of the proposed algorithms.
引用
收藏
页码:2471 / 2479
页数:9
相关论文
共 45 条
[1]   Identification from step responses with transient initial conditions [J].
Ahmed, Salim ;
Huang, Biao ;
Shah, Sirish L. .
JOURNAL OF PROCESS CONTROL, 2008, 18 (02) :121-130
[2]   Novel identification method from step response [J].
Ahmed, Salim ;
Huang, Biao ;
Shah, Sirish L. .
CONTROL ENGINEERING PRACTICE, 2007, 15 (05) :545-556
[3]   Fractional models for modeling complex linear systems under poor frequency resolution measurements [J].
Barbe, Kurt ;
Rodriguez, Oscar J. Olarte ;
Van Moer, Wendy ;
Lauwers, Lieve .
DIGITAL SIGNAL PROCESSING, 2013, 23 (04) :1084-1093
[4]   A new technique to obtain derivative-free optimal iterative methods for solving nonlinear equations [J].
Cordero, Alicia ;
Hueso, Jose L. ;
Martinez, Eulalia ;
Torregrosa, Juan R. .
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2013, 252 :95-102
[5]   Model order formulation of a multivariable discrete system using a modified particle swarm optimization approach [J].
Deepa, S. N. ;
Sugumaran, G. .
SWARM AND EVOLUTIONARY COMPUTATION, 2011, 1 (04) :204-212
[6]   Joint state and multi-innovation parameter estimation for time-delay linear systems and its convergence based on the Kalman filtering [J].
Ding, Feng ;
Wang, Xuehai ;
Mao, Li ;
Xu, Ling .
DIGITAL SIGNAL PROCESSING, 2017, 62 :211-223
[7]   Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering [J].
Ding, Feng ;
Wang, Feifei ;
Xu, Ling ;
Wu, Minghu .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (03) :1321-1339
[8]   Parameter estimation for pseudo-linear systems using the auxiliary model and the decomposition technique [J].
Ding, Feng ;
Wang, Feifei ;
Xu, Ling ;
Hayat, Tasawar ;
Alsaedi, Ahmed .
IET CONTROL THEORY AND APPLICATIONS, 2017, 11 (03) :390-400
[9]   Performance analysis of the generalised projection identification for time-varying systems [J].
Ding, Feng ;
Xu, Ling ;
Zhu, Quanmin .
IET CONTROL THEORY AND APPLICATIONS, 2016, 10 (18) :2506-2514
[10]   Indirect identification of continuous-time delay systems from step responses [J].
Du, Yan Yi ;
Tsai, Jason S. H. ;
Patil, Harshal ;
Shieh, Leang S. ;
Chen, Yuhua .
APPLIED MATHEMATICAL MODELLING, 2011, 35 (02) :594-611