Modeling of single phase inverter of photovoltaic system using Hammerstein–Wiener nonlinear system identification

A Unified Approach for the Identification of Wiener, Hammerstein, and Wiener–Hammerstein Models by Using WH-EA and Multistep Signals

“…where ρl are the estimated model parameters, Z is a twodimensional vector containing the input/output data, n ρl is the number of parameters in the estimated model, N L represents the amount of data used for estimation, V(ρl, Z) is the quadratic-like cost function depending on the difference between measurements and model (ϵ), computed using (10), and p c (n ρl , N L ) is the term known as the corrected penalty and is computed using (11). is used to find the best set of parameters that represent the nonlinear model.…”

“…Static nonlinearities are very common in real systems, and for this reason, block-oriented models have great potential within the identification of nonlinear systems. is class of models has been successfully used in practice including biological processes [4][5][6]; chemical processes [7][8][9]; electronic systems [10,11]; and others [12,13]. Motivation for block-oriented models includes the identification of systems, and many reports of control applications using these types of models can be found in the literature [14][15][16][17][18].…”

System identification with cross validation technique for modeling inverter of photovoltaic system

“…The method is based on nonlinear theory and discrete time systems, treating the system as a black box and model system from measurements of inputs and outputs of systems. Bl ock oriented models [6], the popular model applied in the system identification consist of numbers of linear and nonlinear blocks connected in various cascading and parallel combinations representing the systems such as Wiener model [7], Hammerstein model [8], Wiener-Hammerstein model [9] and Hammerstein-Wiener model [10]. The block oriented models have been attempt to model power electronics modeling but almost of them realize at only one condition such as steady state [11] or transient [12].…”

Two‐step method for identifying photovoltaic grid‐connected inverter controller parameters based on the adaptive differential evolution algorithm

“…In [9], the authors regard the PV grid-connected inverter identification as a black box problem, by using the nonlinear autoregressive with exogenous input (NARX) model to identify non-linear system, one only need to collect the voltage and current data of the inverter, but the fitting degree is relatively low. In [10,11], the authors establish the Hammerstein-Wiener model of single-phase PV inverter.…”