Autonomous Surface Vessel Target Tracking Experiments in Simulated Rough Sea Conditions

Mahini, Farshad; Ashrafiuon, Hashem

doi:10.1115/dscc2012-movic2012-8520

Cited by 5 publications

(8 citation statements)

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“…Recent work in control systems for underactuated marine vehicles has proposed nonlinear set-point control and trajectory tracking Alvarez et al, 2013;Ashrafiuon et al, 2008Ashrafiuon et al, , 2010Do, 2010;Do and Pan, 2003;Mahini andAshrafiuon, 2012, Sonnenburg andWoolsey, 2013). However, few of these control systems have been tested on physical USV platforms (Ashrafiuon et al, 2010).…”

Section: Related Workmentioning

confidence: 98%

“…However, control laws can be derived that are accessible at all points and remain locally controllable (Ashrafiuon, et al, 2010). Recent examples of such control laws include sliding-mode target and trajectory tracking (Ashrafiuon, et al, 2008;Mahini and Ashrafiuon, 2012) as well as Lyapunov-based backstepping techniques that were validated on a model hovercraft. These controllers assumed diagonalized parameter matrices, which may not fully capture the behavior of the physical system.…”

Section: Related Workmentioning

confidence: 99%

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Experimental evaluation of automatically-generated behaviors for USV operations

et al. 2015

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Section: Related Workmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

Experimental evaluation of automatically-generated behaviors for USV operations

et al. 2015

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“…It can be noted that (20) is the same as (17) except for the last term, which includes the bound on the uncertainties and the boundary layer thickness around the sliding surface s, in place of and . The saturation function is used instead of the traditional signum function to reduce the chattering effect [27].…”

Section: Sliding Mode Robust Controlmentioning

confidence: 99%

“…In (20), the bound on the uncertainties acts similarly to controller gains and in (17). The difference is that, once the system enters the boundary layer , a discontinuous control signal is applied, forcing the system to slide along a cross-section of the system normal behavior.…”

Section: Sliding Mode Robust Controlmentioning

confidence: 99%

“…Nonlinear control of unmanned surface vehicles is currently an active area of research, with the majority of the effort devoted towards feedback linearization and backstepping methods [6], [15], [16], [17], [18], [19], [20], as well as sliding mode control [4], [16], [20]. However, the validation of USV control laws is often limited to numerical simulation or small-scale experiments, rather than full-scale sea trials [21].…”

Section: Introductionmentioning

confidence: 99%

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Development of a USV station-keeping controller

Sarda

Bertaska

et al. 2015

OCEANS 2015 - Genova

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The ability of unmanned surface vehicles (USVs) to maintain a fixed orientation and position for an extended period of time is essential for a variety of applications such as acoustic and optical localization and automated launch and recovery of other systems. The need for station-keeping capabilities on USVs requires collaboration between the controller and the propulsion system, both designed to allow the vehicle to perform this challenging maneuver. Small external perturbations, such as wind, waves and current, can have tremendous effects on low weight USVs. These can negatively affect the USV ability to hold its state, resulting in large errors or oscillations. A robust controller capable to account for unmodeled dynamics, which lead to significant deviations between simulated and experimental results, is therefore essential. After an appropriate propulsion system had been designed and installed on a USV, several stationkeeping controllers were implemented and tested. Experimental testing of these controllers in environments of uncertain wind, current and wave disturbances show that the vehicle is best controlled by a nonlinear, backstepping, Multi-Input Multioutput (MIMO) PD controller. A Lagrangian multiplier method was used for control allocation. It is shown that a USV equipped with azimuthing electric propellers is capable to reach and maintain a specific configuration of heading and position for a period of ten or more minutes.

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Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances

Sarda

Bertaska

et al. 2016

Ocean Engineering

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Field trials of a 4 meter long, 180 kilogram, unmanned surface vehicle (USV) have been conducted to evaluate the performance of station-keeping heading and position controllers in an outdoor marine environment disturbed by wind and current. The USV has a twin hull configuration and a custom-designed propulsion system, which consists of two azimuthing thrusters, one for each hull. Nonlinear proportional derivative, backstepping and sliding mode feedback controllers were tested in winds of about 4-5 knots, with and without wind feedforward control. The controllers were tested when the longitudinal axis of the USV was aligned with the mean wind direction and when the longitudinal axis was perpendicular to the mean wind direction. It was found that the sliding mode controller performed best overall and that the addition of wind feedforward control did not significantly improve its effectiveness. However, wind feedforward control did substantially improve the performance of the proportional derivative and backstepping controllers when the mean wind direction was perpendicular to the longitudinal axis of the USV. An analysis of the length scales present in the power spectrum of the turbulent speed fluctuations in the wind suggests that a single anemometer is sufficient to characterize the speed and direction of the wind acting on the USV.

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Autonomous Surface Vessel Target Tracking Experiments in Simulated Rough Sea Conditions

Cited by 5 publications

References 0 publications

Experimental evaluation of automatically-generated behaviors for USV operations

Experimental evaluation of automatically-generated behaviors for USV operations

Development of a USV station-keeping controller

Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances

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