Synchronous generator model identification for control application using volterra series

Application of volterra series for identification of a synchronous generator is investigated in this paper. For linear systems, convolution integral can be used to model the input-output data set. For nonlinear systems, however, volterra series serves as a generalization of the convolution integral. To parameterize the volterra kernels, orthogonal functions have been used. The proposed method is first applied on a seventh order nonlinear model of a synchronous generator with saturation effect and then it is tested on a micro-machine system. In this study, the field voltage is considered as the input and the active output power and the terminal voltage are considered as the outputs of the synchronous generator. Simulation and experimental results show good accuracy of the identified models.