@article{(Open Science Index):https://publications.waset.org/pdf/4693,
	  title     = {Model Predictive Control of Gantry Crane with Input Nonlinearity Compensation},
	  author    = {Steven W. Su  and  Hung Nguyen and  Rob Jarman and  Joe Zhu and  David Lowe and  Peter McLean and  Shoudong Huang and  Nghia T. Nguyen and  Russell Nicholson and  Kaili Weng},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
	    journal   = {International Journal of Mechanical and Mechatronics Engineering},
	  volume    = {3},
	  number    = {2},
	  year      = {2009},
	  pages     = {220 - 224},
	  ee        = {https://publications.waset.org/pdf/4693},
	  url   	= {https://publications.waset.org/vol/26},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 26, 2009},