Identification methods for Hammerstein nonlinear systems

Yapay Ari Koloni̇si̇ Algori̇tmasi İle Opti̇mi̇ze Edi̇len Hammerstein Model Kullanarak Si̇stemleri̇n Ki̇mli̇klendi̇ri̇lmesi̇

“…d(n) is desired system output, y m (n) is model output and e(n) is error value. In identification process, model parameters are defined by minimizing the error (MSE) value between adapted algorithm and system output and model output with the help of a cost function in Equation (13).…”

“…Hammerstein model is a class of block oriented model [13,[26][27][28][29][30][31][32][33]. This model consists of a series connection of a nonlinear sub model followed by a linear sub model.…”

“…System identification is preceded through linear and nonlinear models through the linearity of the system [1][2][3][4][5][6][7][8][9][10][11][12][13]. Linear system identification that the input and the output of the system are stated with linear equations is mostly used because of its advanced theoretical background [1][2][3][4][5][6].…”

“…However, many systems in real life have nonlinear behaviours. Linear methods can be inadequate in identification of such systems and nonlinear methods are used [6][7][8][9][10][11][12][13]. In nonlinear system identification, the input-output relation of the system is provided through nonlinear mathematical assertions as differential equations, exponential and logarithmic functions [14][15][16][17][18].…”

Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

“…The Wiener model and the Hammerstein model are two typical block-oriented nonlinear models [3]. Specifically, the Wiener model consists of a cascade of a linear time invariant (LTI) filter followed by a static nonlinear function, indicated as a linear-nonlinear (LN) model [4][5][6], and the Hammerstein model consists of a cascade of a static nonlinear function follow by a LTI filter, known as a nonlinear-linear (NL) model [7][8][9][10][11][12][13][14][15][16][17][18][19]. Other nonlinear models include neural networks (NNs) [20], Volterra adaptive filters (VAFs) [21], kernel adaptive filters (KAF) [22][23][24][25], among others.…”