Title :
Thruster and vibration control of marine powertrain using a class of feedforward approximators
Author :
Tao, Pey Yuen ; Ge, Shuzhi Sam ; Lee, Tong Heng ; Chen, Xiaoqi
Author_Institution :
Dept. of Electr. & Comput. Eng., National Univ. of Singapore
Abstract :
In this paper, we consider the tracking problem of propeller shaft speed and simultaneously minimizing torsional vibrations in marine shafting system, in the presence of parametric/functional uncertainties and unmodelled dynamics. Torsional vibrations within the shafting system can be induced by the hydrodynamic forces acting on the propeller and the inertia forces of the crank mechanism. Excessive vibrations will lead to severe consequences such as fractured drive shaft and compromised structural integrity. Due to the difficulty in measuring or modelling the hydrodynamic forces as well as the frictional forces, neural networks are used to compensate for the uncertainties. Simulation results illustrate the effectiveness of the proposed controller
Keywords :
feedforward neural nets; marine systems; neurocontrollers; power transmission (mechanical); propellers; shafts; torsion; tracking; vibration control; crank mechanism; feedforward approximator; hydrodynamic force; marine powertrain; marine shafting system; neural networks; propeller shaft speed; thruster control; torsional vibration; vibration control; Control systems; Hydrodynamics; Mechanical power transmission; Neural networks; Propellers; Propulsion; Shafts; Vehicle dynamics; Velocity control; Vibration control;
Conference_Titel :
Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Conference_Location :
Munich
Print_ISBN :
0-7803-9797-5
Electronic_ISBN :
0-7803-9797-5
DOI :
10.1109/CACSD-CCA-ISIC.2006.4777046