Neural Network-Based Adaptive Sigmoid Circular Path-Following Control for Underactuated Unmanned Surface Vessels under Ocean Disturbances

This study describes a circular curve path-following controller for an underactuated unmanned surface vessel (USV) experiencing unmodeled dynamics and external disturbances. Initially, a three degrees of freedom kinematic model of the USV is proposed for marine environmental disturbances and interna...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of marine science and engineering Ročník 11; číslo 11; s. 2160
Hlavní autoři: Ren, Yi, Zhang, Lei, Huang, Wenbin, Chen, Xi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.11.2023
Témata:
Adaptability
Adaptive control
Analysis
Closed loops
Coefficients
Control algorithms
Control equipment
Control systems design
Controllers
Coordinate transformations
Design
Disturbances
Ecosystem disturbance
Feedback control
Fluid mechanics
Guidance (motion)
Hydrodynamic coefficients
Kinematics
Laws, regulations and rules
line of sight
Marine environment
Methods
Neural networks
path following
Proportional derivative
Radial basis function
robust control
Sea vessels
sliding mode
Surface craft
System dynamics
Theoretical analysis
Tracking control
Tracking errors
underactuated unmanned surface vehicle
Velocity
Yaw
Yawing
ISSN:2077-1312, 2077-1312
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This study describes a circular curve path-following controller for an underactuated unmanned surface vessel (USV) experiencing unmodeled dynamics and external disturbances. Initially, a three degrees of freedom kinematic model of the USV is proposed for marine environmental disturbances and internal model parameter deterrence. Then, the circular path guidance law and controller are designed to ensure that the USV can move along the desired path. During the design process, a proportional derivative (PD)-based sigmoid fuzzy function is applied to adjust the guidance law. To accommodate unknown system dynamics and perturbations, a radial basis function neural network and adaptive updating laws are adopted to design the surge motion and yaw motion controllers, estimating the unmodeled hydrodynamic coefficients and external disturbances. Theoretical analysis shows that tracking errors are uniformly ultimately bounded (UUB), and the closed-loop system is asymptotically stable. Finally, the simulation results show that the proposed controller can achieve good control effects while ensuring tracking accuracy and demonstrating satisfactory disturbance rejection capability.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2077-1312
2077-1312
DOI:10.3390/jmse11112160