Neural network-based modelling of a two-degrees-of-freedom twin rotor multiple input, multiple output system using conjugate gradient learning algorithms

2008 ◽  
Vol 222 (6) ◽  
pp. 757-771 ◽  
Author(s):  
A Rahideh ◽  
M H Shaheed
Keyword(s):  
Neural Network ◽  
Conjugate Gradient ◽  
Degrees Of Freedom ◽  
Learning Algorithms ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Output System ◽  
Gradient Learning ◽  
Twin Rotor

Rudder/Fin Roll Stabilization of the USCG WMEC 901 Class Vessel

1999 ◽  
Vol 36 (03) ◽  
pp. 157-170
Author(s):  
Jerrold N. Sgobbo ◽  
Michael G. Parsons
Keyword(s):  
Degrees Of Freedom ◽  
Multiple Input Multiple Output ◽  
Cross Coupling ◽  
Degree Of Freedom ◽  
Rolling Motion ◽  
Rolling Moment ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Three Degree Of Freedom ◽  
The U.S

The U.S. Coast Guard's 270-ft Medium Endurance Cutter (WMEC) operates with an active fin stabilization system. This system was designed using a one-degree-of-freedom (1-DOF) model in the roll direction. The controller was designed separate from the heading autopilot. The effects of the rudders and their ability to produce a significant rolling moment were also neglected as well as the cross coupling of roll motions into other degrees of freedom. This paper studies the effects of the rudders on the rolling motion of the ship using a three-degree-of-freedom (3-DOF) model. A simple optimal heading autopilot is designed and combined with the existing fin roll controller to investigate the effects of the rudders on the roll motions of this class of vessel. A rudder roll controller and a multiple input-multiple output (MIMO) rudder/fin controller are designed as well. Significant roll reduction can be achieved using the MIMO rudder/fin controller.

Sign in / Sign up

Export Citation Format

Share Document