DocumentCode :
574774
Title :
Experimental validation of nonlinear MPC on an overhead crane using automatic code generation
Author :
Vukov, Milan ; Van Loock, Wannes ; Houska, Boris ; Ferreau, Hans Joachim ; Swevers, Jan ; Diehl, Moritz
Author_Institution :
Dept. of Electr. Eng., KULeuven, Leuven, Belgium
fYear :
2012
fDate :
27-29 June 2012
Firstpage :
6264
Lastpage :
6269
Abstract :
Recent advances in improving the efficiency of nonlinear model predictive control (MPC) algorithms have made them suited for challenging mechatronic applications that require high sampling rates. We demonstrate this fact by applying a highly efficient nonlinear MPC algorithm to a laboratory-scale overhead crane setup, featuring a fast moving cart and a winch mechanism. The aim is to perform optimized point-to-point motions with varying line length while respecting actuator limits. In order to solve the resulting optimization problems in less than one millisecond, an automatically generated Gauss-Newton real-time iteration algorithm is employed. We show experimental results illustrating the control performance of the closed-loop system as well as the efficiency of the nonlinear MPC algorithm.
Keywords :
Gaussian processes; actuators; closed loop systems; control engineering computing; cranes; iterative methods; mechatronics; nonlinear control systems; optimisation; predictive control; program compilers; sampling methods; winches; MPC algorithms; actuator limits; automatic code generation; automatically generated Gauss-Newton real-time iteration algorithm; closed-loop system; control performance; experimental validation; fast moving cart; laboratory-scale overhead crane setup; mechatronic applications; nonlinear MPC algorithm; nonlinear model predictive control algorithms; optimization problems; optimized point-to-point motions; sampling rates; varying line length; winch mechanism; Cranes; Mathematical model; Optimal control; Position measurement; Prediction algorithms; Real-time systems; Winches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2012
Conference_Location :
Montreal, QC
ISSN :
0743-1619
Print_ISBN :
978-1-4577-1095-7
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2012.6315390
Filename :
6315390
Link To Document :
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