Identification of fractional Hammerstein system with application to a heating process

被引:43
作者
Hammar, Karima [1 ]
Djamah, Tounsia [1 ]
Bettayeb, Maamar [2 ,3 ]
机构
[1] UMMTO, Lab Concept & Conduite Syst Prod L2CSP, BP 17 RP, Tizi Ouzou 15000, Algeria
[2] Univ Sharjah UAE, Dept Elect & Comp Engn, Sharjah, U Arab Emirates
[3] King Abdulaziz Univ, CEIES, Jeddah, Saudi Arabia
关键词
Nonlinear system; Fractional order system; Hammerstein model; Polynomial nonlinear state-space model; Output-error method;
D O I
10.1007/s11071-019-04946-2
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this paper, fractional Hammerstein system identification is considered, where the linear block is of fractional order. The original discrete Hammerstein system is first converted to a fractional polynomial nonlinear state-space model (PNLSS), which allows a better parameterization of the model. An output-error identification approach is developed based on the robust Levenberg-Marquardt algorithm, whose nevralgic point is the calculation of parametric sensitivity functions. These last are developed as a multivariable fractional PNLSS model which effectively reduces the computational effort. Various simulations are used to test the method's efficiency and its statistical performance is analyzed using Monte Carlo simulation. Finally, the method is evaluated through a heating experimental benchmark. The obtained results show good agreement with the real system outputs.
引用
收藏
页码:2613 / 2626
页数:14
相关论文
共 38 条
[1]  
AOUN Mohamed, 2002, IFAC Proc, V35, P265
[2]   Recursive Least Squares Identification Algorithms for Multiple-Input Nonlinear Box-Jenkins Systems Using the Maximum Likelihood Principle [J].
Chen, Feiyan ;
Ding, Feng .
JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS, 2016, 11 (02)
[3]   Gradient-based parameter estimation for input nonlinear systems with ARMA noises based on the auxiliary model [J].
Chen, Jing ;
Zhang, Yan ;
Ding, Ruifeng .
NONLINEAR DYNAMICS, 2013, 72 (04) :865-871
[4]   Identification for Hammerstein nonlinear ARMAX systems based on multi-innovation fractional order stochastic gradient [J].
Cheng, Songsong ;
Wei, Yiheng ;
Sheng, Dian ;
Chen, Yuquan ;
Wang, Yong .
SIGNAL PROCESSING, 2018, 142 :1-10
[5]  
Cois O., 2001, P EUR CONTR C ECC PO
[6]   An innovative parameter estimation for fractional-order systems in the presence of outliers [J].
Cui, Rongzhi ;
Wei, Yiheng ;
Chen, Yuquan ;
Cheng, Songsong ;
Wang, Yong .
NONLINEAR DYNAMICS, 2017, 89 (01) :453-463
[7]   Modulating function-based identification for fractional order systems [J].
Dai, Yi ;
Wei, Yiheng ;
Hu, Yangsheng ;
Wang, Yong .
NEUROCOMPUTING, 2016, 173 :1959-1966
[8]   Newton iterative identification method for an input nonlinear finite impulse response system with moving average noise using the key variables separation technique [J].
Deng, Kepo ;
Ding, Feng .
NONLINEAR DYNAMICS, 2014, 76 (02) :1195-1202
[9]  
Djamah T., 2008, DES, V42, P939
[10]   Identification of Multivariable Fractional Order Systems [J].
Djamah, Tounsia ;
Bettayeb, Maamar ;
Djennoune, Said .
ASIAN JOURNAL OF CONTROL, 2013, 15 (03) :741-750