Nonlinear State Space Modeling and System Identification for Electrohydraulic Control.

The paper deals with nonlinear modeling and identification of an electrohydraulic control system for improving its tracking performance. We build the nonlinear state space model for analyzing the highly nonlinear system and then develop aHammerstein- Wiener (H-W) model which consists of a static input nonlinear block with two-segment polynomial nonlinearities, a linear timeinvariant dynamic block, and a static output nonlinear block with single polynomial nonlinearity to describe it. We simplify the H-Wmodel into a linear-in-parameters structure by using the key termseparation principle and then use a modified recursive least square method with iterative estimation of internal variables to identify all the unknown parameters simultaneously. It is found that the proposedH-Wmodel approximates the actual system better than the independentHammerstein, Wiener, and ARXmodels. The prediction error of the H-Wmodel is about 13%, 54%, and 58% less than the Hammerstein, Wiener, and ARX models, respectively. [ABSTRACT FROM AUTHOR]