Intelligent UUVs: Some issues on ROV dynamic positioning

Souza, Eric Conrado de; Maruyama, Newton

doi:10.1109/taes.2007.357128

Cited by 34 publications

(12 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…d where I E J\ IS a posItlve an diagonal matrix. Define a Lyapunov function V 2 as 1 T V 2 =Vj +2'eqeq (11) Taking the time derivative of (11) along the dynamics (2) and substituting (10) into it, we have…”

Section: Velocity Control Designmentioning

confidence: 99%

Hierarchical backstepping control for trajectory-tracking of autonomous underwater vehicles subject to uncertainties

Karkoub

2014

2014 14th International Conference on Control, Automation and Systems (ICCAS 2014)

View full text Add to dashboard Cite

In this study, the hierarchical backstepping control (HBC) is used for the trajectory-tracking of autonomous underwater vehicles (AUV) subject to uncertainties (e.g., current disturbances). The proposed HBC utilizes hierarchical structures of the backstepping control based on the kinematic and dynamic models such that both the virtual velocity control and trajectory-tracking of the AUV lead to asymptotic stability. The robustness of the proposed control technique is demonstrated via injection of uncertainties into the closed-loop model. The overall closed-loop stability of the proposed control scheme is guaranteed to have uniformly ultimately bounded (UUB) performance based on the Lyapunov stability criteria. Finally, the feasibility and effectiveness of the proposed scheme are evaluated through computer simulations.

show abstract

Section: Velocity Control Designmentioning

confidence: 99%

Hierarchical backstepping control for trajectory-tracking of autonomous underwater vehicles subject to uncertainties

Karkoub

2014

2014 14th International Conference on Control, Automation and Systems (ICCAS 2014)

View full text Add to dashboard Cite

show abstract

“…2, it can be described by velocity and position vector. Dynamic equations of 6-DOF ROV in coordinate system are as follows [6,7] :…”

Section: B Mathematical Model Of Rov Locationmentioning

confidence: 99%

Q-learning based on particle swarm optimization for positioning system of underwater vehicles

Gao

Chen

et al. 2009

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems

View full text Add to dashboard Cite

The paper presents an intelligent underwater positioning system for remotely operated vehicle (ROV). We used multi-agents reinforcement learning algorithms based on particle swarm optimization fusing signals from Ultra-Short Baseline (USBL) position sonar and pose sensors, so that the USBL can be accelerated and be in-phase with pose sensors. We proposed the frame work of the hardware of the intelligent navigation system, and the multithreading and modularizing software system. Navigation experiment taken in ship model tank indicated the feasibility of the proposed intelligent navigation system.

show abstract

“…But it is not always possible to obtain an accurate ROV's model due to the uncertainties when ROV works in underwater. Many different types of control system methods (Corradini et al, 2011;Souza and Maruyama, 2007;Li et al, 2005;Chin and Lum, 2011) were designed to solve the problem of uncertainty, dynamic positioning and trajectory tracking of the ROV. The proportional-integral-derivative (PID) controller is the most common used controller.…”

Section: Introductionmentioning

confidence: 99%

Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning

Thekkedan

Chin

Woo

2015

J. Marine. Sci. Appl.

View full text Add to dashboard Cite

In this paper, graphical-user-interface (GUI) software for simulation and fuzzy-logic control of a remotely operated vehicle (ROV) using MATLAB TM GUI Designing Environment is proposed. The proposed ROV's GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative (PID) and sliding-mode controller (SMC) systematically and interactively. External disturbance such as sea current can be added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.

show abstract

Intelligent UUVs: Some issues on ROV dynamic positioning

Cited by 34 publications

References 13 publications

Hierarchical backstepping control for trajectory-tracking of autonomous underwater vehicles subject to uncertainties

Hierarchical backstepping control for trajectory-tracking of autonomous underwater vehicles subject to uncertainties

Q-learning based on particle swarm optimization for positioning system of underwater vehicles

Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning

Contact Info

Product

Resources

About