Experimental study on fine motion control of underwater robots

Hanai, Aaron M.; Choi, Hyun‐Taek; Choi, Sang Jun; Yuh, J.

doi:10.1163/1568553042674680

Cited by 13 publications

(8 citation statements)

References 3 publications

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“…The vehicle's actuation is represented by 3 independent forces and 3 independent moments about the center of mass of the vehicle. A thruster mapping algorithm, such as the one described in [33], can be used to map the controlled forces and moments onto a custom thruster configuration for the AUV. The external disturbance for the simulation is represented by The control gains for the NN feedforward term are selected as Γ 1 = 2000 · I 6×6 , Γ 2 = 500 · I 6×6, where I i×i denotes the identity matrix of size i by i.…”

Section: Simulation Resultsmentioning

confidence: 99%

Nonlinear control of an autonomous underwater vehicle: A RISE-based approach

Fischer

Bhasin

Dixon

2011

Proceedings of the 2011 American Control Conference

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Autonomous and remotely operated marine vehicles such as ships and submarines are becoming a key component in several aspects of maritime industry and defense. This paper explores the development of a nonlinear controller for a fully actuated autonomous underwater vehicle (AUV) using a robust integral of the sign of the error (RISE) feedback term with a neural network (NN) based feedforward term to achieve semi-global asymptotic tracking results in the presence of complete model uncertainty and unknown disturbances. A simulation is provided to demonstrate the proposed controller on an experimentally validated AUV model.

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Section: Simulation Resultsmentioning

confidence: 99%

Nonlinear control of an autonomous underwater vehicle: A RISE-based approach

Fischer

Bhasin

Dixon

2011

Proceedings of the 2011 American Control Conference

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“…The controller described in this paper is most closely related to work by Hanai et al [8]. They propose a similar geometric solution to robot control.…”

Section: Related Workmentioning

confidence: 95%

“…Our method is related to, but differs from Hanai et al [8] in that they directly compute the required thrust necessary to be produced by each thruster. Hanai et al assume that the voltage-to-thrust curve is known and drive each thruster directly from this curve.…”

Section: B Overviewmentioning

confidence: 99%

“…Adding constraints to A rot are one way of choosing the right solution. Alternatively, as in [8] a specific solution can be chosen (for example to minimize the thruster output while avoiding thruster dead bands). We have chosen the constraint adding solution because in our experiences thruster dead bands did not affect the performance of our robot.…”

Section: Computing the Attitude Errormentioning

confidence: 99%

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Complete SE<sup>3</sup> underwater robot control with arbitrary thruster configurations

Doniec

Vasilescu

Detweiler

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-We present a control algorithm for autonomous underwater robots with modular thruster configuration. The algorithm can handle arbitrary thruster configurations. It maintains the robot's desired attitude while solving for translational motion. The attitude can be arbitrarily chosen from the special orthogonal group SO 3 allowing the robot all possible orientations. The desired translational velocities can be chosen from R 3 allowing the robot to follow arbitrary trajectories underwater. If the robot is not fully holonomic then the controller chooses the closest possible solution using least squares and outputs the error vector.We verify the controller with experiments using our autonomous underwater robot AMOUR. We achieve roll errors of 1.0 degree (2.1 degrees standard deviation) and pitch errors of 1.5 degrees (1.8 degrees standard deviation). We also demonstrate experimentally that the controller can handle both nonholonomic and fully holonomic thruster configurations of the robot. In the later case we show how depth can be maintained while performing 360 degree rolls. Further, we demonstrate an input device that allows a user to control the robot's attitude while moving along a desired trajectory.

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“…The vehicle has physical dimensions of 1.3 m × 0.5 m × 0.5 m and is configured with eight bidirectional thrusters in a redundant configuration with four heave thrusters, two sway thrusters, and two primary surge thrusters, allowing for maneuvering in 6 DOF. The relationship between the force/moment acting on the vehicle and the control input of each individual thruster can be described by a thruster mapping algorithm, such as the one described in [39].…”

Section: A Vehicle Configurationmentioning

confidence: 99%

Nonlinear RISE-Based Control of an Autonomous Underwater Vehicle

et al. 2014

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Abstract-This study focuses on the development of a nonlinear control design for a fully-actuated autonomous underwater vehicle (AUV) using a continuous robust integral of the sign of the error control structure to compensate for system uncertainties and sufficiently smooth bounded exogenous disturbances. A Lyapunov stability analysis is included to prove semiglobal asymptotic tracking. The resulting controller is experimentally validated on an AUV developed at the University of Florida in both controlled and open-water environments.Index Terms-Autonomous underwater vehicles (AUVs), marine robotics, nonlinear control, robust integral of the sign of the error (RISE).

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Experimental study on fine motion control of underwater robots

Cited by 13 publications

References 3 publications

Nonlinear control of an autonomous underwater vehicle: A RISE-based approach

Nonlinear control of an autonomous underwater vehicle: A RISE-based approach

Complete SE<sup>3</sup> underwater robot control with arbitrary thruster configurations

Nonlinear RISE-Based Control of an Autonomous Underwater Vehicle

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