A Local Nonlinear Model for the Approximation and Identification of a Class of Systems

The special form of the Laplace-domain Volterra kernels for linear-analytic systems is exploited to obtain an approximate model that obeys an appealingly simple feedforward block structure. It comprises a composition of the linearization and the multivariate nonlinear function of the original system. The model does not involve a truncation in the power series expansion nor in the memory depths and offers an economic parameterization. It is shown to be linearly identifiable in one step if
a

priori
information about the linearized dynamics is provided. We present simulation results for a simple nonlinear circuit showing the validity of the model.