Stable antiswing PD control for overhead crane systems with velocity estimation and uncertainties compensation Online publication date: Sun, 25-Nov-2007
by Rigoberto Toxqui, Wen Yu, Xiaoou Li
International Journal of Automation and Control (IJAAC), Vol. 1, No. 4, 2007
Abstract: In this paper, we propose a novel model-free control for overhead crane system. This controller includes position regulation and antiswing control. Since the crane model is unknown, Radial Basis Function (RBF) neural networks are used to compensate friction, gravity and coupling between position and antiswing control. High-gain observer is applied to estimate the joint velocities to realise Proportional and Derivative (PD) control. Real-time experiments are presented to compare our stable antiswing PD control with other normal crane controllers.
Online publication date: Sun, 25-Nov-2007
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