Paper Info
Title
Intelligent rudder control of an unmanned surface vessel.
Abstract
Trajectory tracking control of unmanned surface vessels (USV) is addressed.Gain scheduling PID optimized by GA and fuzzy logic controllers applied to USV.Novel and efficient combination of conventional and intelligent for rudder control.Model generated from real data of a scale replica of the operational ship.Control actions feasible as actuator saturation is included. Trajectory tracking control for unmanned marine surface vessels (USV) is quite complex because of the strongly non-linearity of the system and the presence of uncertainties and environmental changing conditions. To face those issues, in this paper intelligent and conventional strategies are used as the main control framework for the rudder angle of an USV. The guidance law calculates the desired angle and estimates the trajectory based on the dynamic model of the autonomous ship, which has been generated from real data obtained from experiments with a scale prototype. The model accounts for the physical limitations of both the rudder and the ship propulsion system. An adaptive control law is first proposed which is suitable for any different trajectory and can deal with varying path shapes. This gain scheduling approach utilizes PID controllers whose tuning parameters have been optimized by genetic algorithms (GA) for the different operation points (GS-PID-GA). Besides, a fuzzy logic controller (FLC) is designed to deal with the uncertainties of the dynamics and to include the expertise of an operator. Simulations validate the effectiveness of the proposed control approaches that have been compared with conventional control.
Year
DOI
Venue
2016
10.1016/j.eswa.2016.01.057
Expert Syst. Appl.
Keywords
Field
DocType
Intelligent control,Gain scheduling,Fuzzy logic,Genetic algorithms,Trajectory tracking,Unmanned surface vessel (USV)
Intelligent control,Rudder,Propulsion,PID controller,Computer science,Gain scheduling,Control theory,Fuzzy logic,Adaptive control,Trajectory
Journal
Volume
Issue
ISSN
55
C
0957-4174
Citations 
PageRank 
References 
10
0.80
8
Authors
2
Name
Order
Citations
PageRank
J. Menoyo Larrazabal1100.80
Matilde Santos Peñas2255.08