A Self Learning Fuzzy Logic Controller for Ship Steering System

2012 ◽  
Vol 8 (1) ◽  
pp. 25-34
Author(s):  
Ammar A. Aldair
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Steering System ◽  
Ship Steering ◽  
Self Learning

scholarly journals A Self Learning Fuzzy Logic Controller for Ship Steering System

2012 ◽  
Vol 8 (8) ◽  
pp. 25-34
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Ad Hoc ◽  
High Efficiency ◽  
Fuzzy Controller ◽  
Steering System ◽  
Intelligent Control System ◽  
Ship Steering ◽  
Self Tuning ◽  
Self Learning

A self learning fuzzy logic controller for ship steering systems is proposed in this paper. Due to the high nonlinearity of ship steering system, the performances of traditional control algorithms are not satisfactory in fact. An intelligent control system is designed for controlling the direction heading of ships to improve the high efficiency of transportation, the convenience of manoeuvring ships, and the safety of navigation. The design of fuzzy controllers is usually performed in an ad hoc manner where it is hard to justify the choice of some fuzzy control parameters such as the parameters of membership function. In this paper, self tuning algorithm is used to adjust the parameters of fuzzy controller. Simulation results show that the efficiency of proposed algorithm to design a fuzzy controller for ship steering system.

A self-learning fuzzy logic controller using genetic algorithms with reinforcements

1997 ◽  
Vol 5 (3) ◽  
pp. 460-467 ◽  
Author(s):  
Chih-Knan Chiang ◽  
Hung-Yuan Chung ◽  
Jin-Jye Lin
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Self Learning

Robustness Study of an On-Line Application of a Self-Learning Fuzzy Logic Controller

1996 ◽  
Vol 29 (1) ◽  
pp. 5363-5368
Author(s):  
S.H. Ghwanmeh ◽  
K.O. Jones ◽  
D. Williams
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
On Line ◽  
Self Learning

Design of Fuzzy Logic Controller for Four Wheel Steering System

2005 ◽  
Author(s):  
Evren Ozatay ◽  
Samim Y. Unlusoy ◽  
Murat A. Yildirim
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Steering System ◽  
Front Wheel ◽  
Sideslip Angle ◽  
Yaw Rate ◽  
Nonlinear Vehicle Model ◽  
Three Degree Of Freedom ◽  
Vehicle Dynamics Control

Integration of the driver’s steering input together with the four-wheel steering system (4WS) in order to improve the vehicle’s dynamic behavior with respect to yaw rate and body sideslip angle is possible with intelligent vehicle dynamics control systems. The goal of this study is to develop a fuzzy logic controller for this purpose. In the first stage of the study, a three-degree of freedom nonlinear vehicle model including roll dynamics is developed. The Magic Formula is applied in order to formulate the nonlinear characteristics of the tires. In the design of the fuzzy logic controller, a two-dimensional rule table is created based on the error and on the change in the error of sideslip angle, which is to be minimized. Fuzzy logic controlled model is then compared with front wheel steering vehicle and the vehicles having different control strategies that have previously been studied in literature. Simulations indicate that fuzzy logic controlled vehicle can provide zero body sideslip angle in transient motion and quick response in terms of yaw rate during steady state cornering and lane change maneuvers.

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