A hybrid dynamic model and parameter estimation method for accurately simulating overhead cranes with friction
Jorge Vicente-Martinez, Edgar Ramirez-Laboreo
公開日: 2025/9/8
Abstract
This paper presents a new approach to accurately simulating 3D overhead cranes with friction. Nonlinear friction dynamics have a significant impact on these systems, however, accurately modeling this phenomenon in simulations is a significant challenge. Traditional methods often rely on imprecise approximations of friction or require excessive computational times for reliable results. To address this, we present a hybrid dynamical model that features a trade-off between high-fidelity friction modeling and computational efficiency. Furthermore, we present a step-by-step algorithm for the comprehensive estimation of all unknown system parameters, including friction. This methodology is based on Gaussian Process Regression (GPR) and Least Squares (LS) estimations. Finally, experimental validation with a laboratory crane confirms the effectiveness of the proposed modeling and estimation approach.