Improved Discrete Techniques of Time‐Delay and Order Estimation for Large‐Scale Interconnected Nonlinear Systems

Abstract

The selection of a suitable model structure is an essential step in system modeling. Model structure is defined by determining the class, the time delay, and the model order. This paper proposes improved structural estimation procedures for large-scale interconnected nonlinear systems which are composed of a set of interconnected Single-Input Single-Output (SISO) Hammerstein structures and described by discrete-time stochastic models with unknown time-varying parameters. An extensive Determinant Report (DR) algorithm is developed to determine the order of the process. An improved discrete-time technique based on Recursive Extended Least Squares with Varying Time (RELSVT) delay method is proposed to estimate the time delays of the considered system. The developed theoretical analysis and simulation results prove the validity and performance of the proposed algorithms.

Joint tracking coefficients and the time delay of a nonstationary linear system, preceded by a static nonlinearity

“…There is a large amount of references available on different approaches of parametric identification of block‐oriented Hammerstein systems, as important models of plants, functioning in real time. Considering the scope of published materials, we have mentioned here just a few ones, approaches of which could be related with the adaptive parametric identification 18‐28 . However, our position is restricted to Hammerstein systems with the time‐varying delayed argument in a linear part, which delivered new aspects discussed, by Ferretti et al, 29 Richard, 30 and Gao and Karimi 31…”