Dual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems

Author(s):  
D. Sbarbaro
2015 ◽  
Vol 89 (3) ◽  
pp. 611-622 ◽  
Author(s):  
Houda Salhi ◽  
Samira Kamoun ◽  
Najib Essounbouli ◽  
Abdelaziz Hamzaoui

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Houda Salhi ◽  
Samira Kamoun

This paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic idea is to estimate jointly the parameters, the state vector, and the internal variables of MIMO Wiener models based on a specific decomposition technique to extract the internal vector and avoid problems related to invertibility assumption. The effectiveness of the proposed algorithms is shown by an illustrative simulation example.


2014 ◽  
Vol 134 (11) ◽  
pp. 1708-1715
Author(s):  
Tomohiro Hachino ◽  
Kazuhiro Matsushita ◽  
Hitoshi Takata ◽  
Seiji Fukushima ◽  
Yasutaka Igarashi

2012 ◽  
Vol 132 (6) ◽  
pp. 913-918 ◽  
Author(s):  
Kayoko Hayashi ◽  
Toru Yamamoto ◽  
Kazuo Kawada

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