Continuous-time approaches to system indentification—a survey
Automatica (Journal of IFAC) - Identification and system parameter estimation
Identification of Continuous-time Models from Sampled Data
Identification of Continuous-time Models from Sampled Data
IIR Volterra filtering with application to bilinear systems
IEEE Transactions on Signal Processing
Hi-index | 22.14 |
We present a time-continuous identification method for nonlinear dynamic Volterra models of the form HX=f(u,X)+v with H, a causal convolution operator. It is mainly based on a suitable parameterization of H deduced from the so-called diffusive representation, which is devoted to state representations of integral operators. Following this approach, the complex dynamic nature of H can be summarized by a few numerical parameters on which the identification of the dynamic part of the model will focus. The method is validated on a physical numerical example.