International Journal of Robust and Nonlinear Control, Journal Year: 2025, Volume and Issue: unknown
Published: May 9, 2025
ABSTRACT Nonlinear system identification plays a key role in real‐world modeling. The spline networks can model the nonlinearity with high precision without prior knowledge of nonlinear structure. This paper examines problem Hammerstein systems outliers by using to describe nonlinearity. To avoid redundant computation, two sub‐models are derived, one local parameters and other global linear parameters. By exploiting insensitivity correntropy outliers, correntropy‐based robust interval‐varying recursive estimation method is presented. proposed not only models unknown computational efficiency but also under premise that total distribution observed data unknown. superiority algorithm validated simulation experiments.
Language: Английский