The Research On Identification And Control For Nonlinear Hammerstein-Wiener System

Ideal linear control system does not exist in practical industrial system, and industrial objects often have obviously nonlinear characteristics. Therefore, the identification, modeling and adaptive control of nonlinear systems has become the research focus for the control theory of non-linear model.It has been found that Hammerstein-Wiener type usually may account for experimental model of nonlinear systems. It is composed of a nonlinear static element, a linear dynamic element and another nonlinear static element connected in series, characterized by nonlinear static character and linear dynamic character considered respectively, thus varieties of nonlinear systems can be described simply and effectively so that the majority of nonlinear characteristics of the process of industrial production can be reflected precisely. For example, the system mode would be more similar to the actual situation with the higher accuracy by representing the electrode regulator system of the EAF steelmaking process as Hammerstein-Wiener model.First, the researching background, the status quo of the nonlinear system identification and controlling method and the content of the paper are described. Then a theory based on least squares support vector machine identification and two-step generalized predictive control for Hammerstein-Wiener system is studied.Using least squares support vector machine method, the identification problem is converted into a constrained optimization problem by assuming collinear constraints based on this method, avoiding the iterative calculation to identify Hammerstein-Wiener system previously. In the same time, the electrode regulator system of the arc furnace steel-making process followed Hammerstein-Wiener type essentially can be identified, and studies with MATLAB simulation demonstrate that the proposed identification method is available.Using two-step generalized predictive control, the Hammerstein-Wiener model of the linear part and nonlinear part are considered separately, and the control problem is resolved into the dynamic optimization problem of a linear model and the problem of solution of nonlinear static model, so the treatment is fairly flexible and every step of the algorithm can be chosen flexibly. In the same time, the electrode regulator system of the arc furnace steel-making process followed Hammerstein-Wiener type essentially can be controlled, and studies with MATLAB simulation demonstrate that the proposed identification method is available.