DocumentCode :
3217350
Title :
Anti-rolling fin control for ship stabilization
Author :
Kuo-Ho Su
Author_Institution :
Grad. Inst. of Digital Mechatron. Technol., Chinese Culture Univ., Taipei, Taiwan
fYear :
2013
fDate :
2-4 Dec. 2013
Firstpage :
389
Lastpage :
394
Abstract :
Active fin control is the most effective anti-rolling approach for ship stabilization system, however the accurate model of whole nonlinear dynamic ship system under random wave or wind impact is difficult to obtain. In this paper, a guarded heuristic genetic algorithm fin controller (GHGAFC) including a heuristic genetic algorithm fin controller (HGAFC) and a guarded fin controller (GFC) is developed for ship stabilization system. In the HGAFC design, the gradient descent training is embedded into conventional genetic algorithm (GA) to construct a main controller to search the optimum fin control angle under the occurrence of uncertainties. In order to ensure the system states around a defined bound region, a guarded fin controller (GFC) is added to adjust the control angle. In the stabilization system, the gyroscope and accelerometer are used to detect the swaying conditions and the gathered data are sent to embedded microcontroller to calculate the command. To verify the effectiveness of the proposed fin controller, some simulations are carried out under the assumption that the sea surface is modeled as a one-dimension linear free surface. The performance is also compared with other announced GA-fuzzy, GA-PID and conventional supervisory GA control schemes under the same conditions.
Keywords :
genetic algorithms; motion control; nonlinear control systems; ships; stability; GA-PID; GA-fuzzy; active fin control; anti-rolling fin control; conventional supervisory GA control; embedded microcontroller; gradient descent training; guarded heuristic genetic algorithm fin controller; nonlinear dynamic ship system; one-dimension linear free surface; random wave impact; ship stabilization system; wind impact; Actuators; Biological cells; Equations; Genetic algorithms; Marine vehicles; Nonlinear dynamical systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Control Conference (CACS), 2013 CACS International
Conference_Location :
Nantou
Print_ISBN :
978-1-4799-2384-7
Type :
conf
DOI :
10.1109/CACS.2013.6734166
Filename :
6734166
Link To Document :
بازگشت