Volterra Series Models for Nonlinear Automatic Control Systems

The paper presents algorithms for constructing nonlinear integral models based on the Volterra series tool. Modeling of dynamic processes means assessing the response to possible external changes in real time. The vector of input signals may include measured influences and control actions to be identified based on an analysis of the current state. We use identification algorithms based on the theory of Volterra polynomial equations of the first kind. An approach to the approximate solution to selected types of nonlinear systems of Volterra integral equations using the Newton-Kantorovich method is presented. We use the numerical solution to the corresponding linear system of equations as a trial solution. Calculation schemes obtained with help the standard quadrature methods are given.