The problem of nonlinear dynamic systems modelling by means of block-oriented models has been strongly elaborated for the last four decades, due to vast variety of applications. The concept of block-oriented models assumes that the real plant, as a whole, can be treated as a system of interconnected blocks, static nonlinearities (N) and linear dynamics (L), where the interaction signals cannot ...

This paper introduces a new approach to controlling Pressure Swing Adsorption (PSA) using neural network controller based on Model Predictive Control (MPC) process. We use Hammerstein–Wiener (HW) model representing the real PSA process data. Then, we design an MPC-controlled HW maintain bioethanol purity near 99% molar fraction. work proposes Artificial Neural Network (ANN) that captures dynami...

This paper considers an iterative algorithm for the identification of structured nonlinear systems. The systems considered consist of the interconnection of a MIMO linear systems and a MIMO nonlinear system. The considered interconnection structure can represent as particular cases Hammerstein, Wiener or Lur’e systems. A key feature of the proposed method is that the nonlinear subsystem may be ...

Abstract. Application of least squares and instrumental variables to recovering parameters of nonlinear complex dynamic block-oriented systems is examined. For a system with the Hammerstein-Wiener structure the instrumental variable algorithm is designed and compared with the least squares algorithm for estimating system parameters. The advantages of the proposed instrumental variable estimator...

In this paper, we consider a new method for modeling and equalizing of nonlinear wireless channel. The Volterra structure equalizer has high computation burden and slow convergence rate due to its large number of coefficients and the pre-distortion method is very difficult to realize in actual wireless communication systems. Here, we take another scheme instead of those above. First assume the ...