Parameter estimation of nonlinear continuous-time systems using Hartley modulating functions

Identification of a class of nonlinear continuous time systems using Hartley modulating functions (HMF) is one of the recently developed methodologies proposed by A. Patra and H. Unbehauen (1995). This new methodology is applicable to a large class of nonlinear continuous time systems by defining a set of HMF for characterizing the continuous process signals. The method is re examined and further developed; specifically, the convergence difficulties for noisy output signals are distinctly improved with an efficient formulation of the least squares parametric identification algorithm for integrable and convolvable nonlinear continuous time systems, assuming white measurement noise. Moreover, the paper investigates the capability of this parameter estimation method on a class of nonlinear continuous time systems which are linear in their parameters. Several simulation examples are also considered in this work to examine the performance of the proposed estimation method.