Title: Stable antiswing PD control for overhead crane systems with velocity estimation and uncertainties compensation
Authors: Rigoberto Toxqui, Wen Yu, Xiaoou Li
Addresses: Departamento de Control Automatico, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, Mexico D.F. 07360, Mexico. ' Departamento de Control Automatico, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, Mexico D.F. 07360, Mexico. ' Departamento de Computacion, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, Mexico D.F., 07360, Mexico
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.
Keywords: anti-swing control; overhead cranes; PID control; stability; neural networks; high-gain observer; velocity estimation; uncertainty compensation; model-free control.
International Journal of Automation and Control, 2007 Vol.1 No.4, pp.342 - 357
Published online: 25 Nov 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article