Call For Paper Volume:4 Issue:10 Oct'2017 |

Nonlinear Identification of A Wireless Control System: Hammerstein-Wiener Modeling

Publication Date : 18/09/2015



Author(s) :

Adnan Aldemir , Mustafa Alpbaz.


Volume/Issue :
Volume 2
,
Issue 9
(09 - 2015)



Abstract :

This study proposes to modeling a process simulator that was used for the wireless control by using a nonlinear system identification technique based on Hammerstein-Wiener model. Wireless input/output data obtained from the Cussons P3005 type process control simulator. Wireless temperature experiments were achieved by using MATLAB/Simulink program and wireless data transfer during the experiments were carried out with radio waves at a frequency of 2.4 GHz. Hammerstein-Wiener model orders and three estimator types were applied with the aid of System Identification Toolbox (SIT) of MATLAB using the wireless data acquired from the process simulator. It was observed that the fit values of the piecewise linear estimator type which was calculated for T2, T3 and T4 were higher than that of the dead zone and saturation model. According to the results the highest fit values are determined with piecewise linear estimator type which is calculated by 2, 2 and 1 model orders nb, nf and nk, respectively. The best accuracy, loss function and final prediction error values for T2 are determined 97.45, 0.249 and 0.252, for T3 are determined 92.72, 1.053 and 1.126 and for T4 are determined 86.56, 3.488 and 3.539, respectively. After determined of the best model order and estimator type for this wireless system was analyzed and characterized by graphical tools which can be used to design the linear controller, stability analysis, causality, system response analysis and signal processing. Keywords—Nonlinear system identification, Hammerstein-Wiener model, MATLAB/Simulink, wireless process control, final prediction error, fit value, loss function


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Nonlinear Identification of A Wireless Control System: Hammerstein-Wiener Modeling

September 16, 2015