Abstract
The analysis and identification of separable nonlinear single valued systems is carried out from a functional standpoint, by modifying the Volterra series to separate bias and steady state gain from dynamic effects. This analysis is applied to the development of generalised expressions for output bias, variance and correlation functions of nonlinear systems with Gaussian or pseudo-random inputs. An identification procedure is then developed and applied to the testing of both simulated systems, and an electrohydraulic servomotor. An error analysis is carried out showing the limitations of the method, and procedures derived designed at eliminating the effects of random and cyclic noise.