From PD to Nonlinear Adaptive Depth-Control of a Tethered Autonomous Underwater Vehicle

Maalouf, Divine; Tamanaja, Ivan Torres; Campos, E.; Chemori, Ahmed; Creuze, Vincent; Sánchez‐Torres, Juan Diego; Lozano, Rogelio

doi:10.3182/20130204-3-fr-2033.00085

Cited by 20 publications

(9 citation statements)

References 10 publications

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“…The nonlinear compensation is given in equation (8). The At the end, the proposed model, equation (10), is a linear system with uncertainties.…”

Section: Fig 3 Robust Controller and Nonlinear Compensatormentioning

confidence: 99%

“…In SAUC-E [6] and euRathlon [7] competitions, we concluded that PID yaw controller was less efficient for low mass AUV. Consequently, advanced control algorithms should be involved, such as the adaptive control scheme in [8], robust control scheme in [9] and interval analysis approach in [10]. Note that robust control schemes are shown to be successfully in [11] and [12] for torpedo-shaped AUVs.…”

Section: Introductionmentioning

confidence: 99%

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Robust heading control and its application to Ciscrea Underwater Vehicle

Yang

Clément

Mansour

et al. 2015

OCEANS 2015 - Genova

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Deep inside the ocean, the earth magnetic signal is one of the merely existing information that tells the heading of robots with very good cost efficiency. Therefore, this paper focuses on the AUV (Autonomous Underwater Vehicle) heading control problem using only one magnetic compass as feedback sensor. In this application, we address AUV modeling and control issues simultaneously. Because of quadratic damping factor, underwater vehicle hydrodynamic model is nonlinear. In addition, unmodeled dynamics, parameter variations and environmental disturbances create significant uncertainties between the nominal AUV model and the reality. Finally, sensor noise, signal delay as well as unmeasured states also affect the stability and control performance of AUV motions. In order to handle these issues with improved AUV observation quality and navigation ability, we propose a CFD (Computational Fluid Dynamics) model based H ∞ robust control scheme.Without loss of generality, the robust heading controller was implemented and validated in the sea on low-mass and complex-shaped Ciscrea AUV. Simulation and sea experimental results of both PID (Proportional Integral Derivative) and robust heading controller are analysed.

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“…The nonlinear compensation is given in equation (8). The At the end, the proposed model, equation (10), is a linear system with uncertainties.…”

Section: Fig 3 Robust Controller and Nonlinear Compensatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust heading control and its application to Ciscrea Underwater Vehicle

Yang

Clément

Mansour

et al. 2015

OCEANS 2015 - Genova

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“…In [1] an experimental evaluation of an AMBC is reported during simultaneous motion in the translational DOF. Comparative experimental evaluations of linear controllers, model-based controllers and their adaptive extensions for UV single DOF motion have been reported [13], [25]. In [33] a comparative experimental evaluation in the presence of a common external disturbance for proportional integral derivative control, disturbance observer control and the adaptive extensions of both is reported.…”

Section: B Literature Reviewmentioning

confidence: 99%

Experimental evaluation of adaptive model-based control for underwater vehicles in the presence of unmodeled actuator dynamics

McFarland

Whitcomb

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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This paper reports a comparative experimental evaluation of proportional derivative and adaptive modelbased control for underwater vehicles. To the best of the authors' knowledge, this is the first such evaluation of modelbased adaptive tracking control for underwater vehicles during simultaneous dynamic motion in all 6 degrees-of-freedom. This experimental evaluation revealed the presence of unmodeled thruster dynamics arising during reversals of the vehicle's thrusters, and that the unmodeled thruster dynamics can destabilize parameter adaptation. The three major contributions of this paper are: an experimental analysis of how unmodeled thruster dynamics can destabilize parameter adaptation, a twostep adaptive model-based control algorithm which is robust to the thruster modeling errors present, and a comparative experimental evaluation of adaptive model-based control and proportional derivative control for fully-actuated underwater vehicles preforming simultaneous 6 degree-of-freedom trajectory tracking. I. INTRODUCTIONThis paper addresses the problem of adaptive modelbased trajectory tracking control of Underwater Vehicles (UV) for dynamic 6 degree-of-freedom (DOF) motion. The approach of adaptive model-based control (AMBC) refines estimates of plant parameters during the trajectory tracking control process. The adaptive controller estimates parameters for a rigid-body plant such as vehicle mass with added hydrodynamic mass, quadratic drag, gravitational force, and buoyancy torque parameters that arise in the dynamic models of rigid-body UV. We report a comparative experimental evaluation of AMBC and proportional derivative control (PDC) in full scale vehicle trials utilizing the Johns Hopkins University Hydrodynamic Test Facility and Johns Hopkins University Remotely Operated Vehicle (JHU ROV) (Fig. 1). This experimental evaluation shows that AMBC provides 30% better position tracking performance and 8% worse velocity tracking performance over PDC. To the best of the authors' knowledge, this is the first experimental comparison of AMBC and PDC during simultaneous motion in all DOF.

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“…The most basic task of this card is to balance the vehicle with the PID control system by using the data it receives from IMU. The PID control method is a feedback control mechanism commonly used in industrial control systems (Johnson & Moradi, 2005;Maalouf et al, 2013;Shen, Cao, Zhou, Xu, & Gu, 2013). A PID controller calculates an "error" value by taking the difference between the measured value and the desired reference value.…”

Section: Water Vehicles Communication Systemsmentioning

confidence: 99%

İnsansız Su Altı Araçlarında Haberleşme ve Güç Sistemlerinin Tasarımı

Ataner

Özdeş

Öztürk

et al. 2020

European Journal of Science and Technology

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Unmanned underwater vehicles (ROV/AUV) are robotic systems that can float underwater, are autonomous and remotely controlled. The first unmanned underwater vehicle on record was designed by Luppis Whitehead Automobile in the form of a torpedo in 1864. The first vehicle designed in the same sense used today was designed by Dimitri Rebikoff in 1953. Today, unmanned underwater vehicles are used in a wide range of areas such as underwater search and rescue operations, ship underwater maintenance and repair operations, taking images from dangerous environments where divers cannot enter, military use, inspection of wrecks and underwater cleaning. The design stages of underwater vehicle control system are given in this study. The system consists of control cards, communication modules, sensors, lighting and power electronics elements. The basic philosophies followed for the design of the system are modularity and safety. This situation provides ease in the organization of the components in the underwater vehicle as well as the modular structure, the test and repair stages are easily carried out. To ensure modularity, the system is divided into two subcomponents as power and control units. In addition, a computer interface is used to control the underwater vehicle. With this interface, data is exchanged with underwater vehicles so that the depth, water temperature and temperature of the sealed tube containing the electronic components can be monitored. Another task of the computer interface is to transfer the camera image taken from underwater to the user. In this study, the remote control of unmanned underwater vehicles, the power system, communication infrastructure, the design of the structure that provides the transmission of the image and sensor information taken from underwater is mentioned.

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From PD to Nonlinear Adaptive Depth-Control of a Tethered Autonomous Underwater Vehicle

Cited by 20 publications

References 10 publications

Robust heading control and its application to Ciscrea Underwater Vehicle

Robust heading control and its application to Ciscrea Underwater Vehicle

Experimental evaluation of adaptive model-based control for underwater vehicles in the presence of unmodeled actuator dynamics

İnsansız Su Altı Araçlarında Haberleşme ve Güç Sistemlerinin Tasarımı

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