Generalized Laguerre Reduction of the Volterra Kernel for Practical Identification of Nonlinear Dynamic Systems
This work addresses the computational complexity in system identification for engineers and researchers, though it appears incremental as it extends existing Laguerre-based methods to a more general MIMO framework.
The paper tackles the problem of reducing the number of coefficients needed to model nonlinear dynamic systems using Volterra series by introducing a novel algorithm for generalized calculation of finite-order Volterra-Laguerre series for MIMO systems, with an example demonstrating its practical utility.
The Volterra series can be used to model a large subset of nonlinear, dynamic systems. A major drawback is the number of coefficients required model such systems. In order to reduce the number of required coefficients, Laguerre polynomials are used to estimate the Volterra kernels. Existing literature proposes algorithms for a fixed number of Volterra kernels, and Laguerre series. This paper presents a novel algorithm for generalized calculation of the finite order Volterra-Laguerre (VL) series for a MIMO system. An example addresses the utility of the algorithm in practical application.