A hybrid dynamic model and parameter estimation method for accurately simulating overhead cranes with friction
For engineers simulating overhead cranes, this method improves simulation accuracy of friction dynamics without excessive computational cost.
The paper presents a hybrid dynamic model and parameter estimation method for 3D overhead cranes with friction, achieving accurate simulation with a trade-off between fidelity and computational efficiency. Experimental validation on a laboratory crane confirms effectiveness.
This paper presents a new approach to accurately simulating 3D overhead cranes with friction. Although nonlinear friction dynamics has a significant impact on these systems, 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 Bayesian Linear Regression and Least Squares (LS) estimations. Finally, experimental validation with a laboratory crane confirms the effectiveness of the proposed modeling and estimation approach.