Command Governor Adaptive Control for Unmanned Underwater Vehicles with measurement noise and actuator dead-zone

Makavita, Charita D.; Nguyen, HD; Jayasinghe, Shantha Gamini; Ranmuthugala, Dev

doi:10.1109/mercon.2016.7480171

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…Remark The contributions of the work could be explained in theoretical and practical aspects 22‐24 . From the practical point of view, autonomous marine vehicles are widely applied in precise underwater manoeuvring process including underwater oil rigs, mine development and so forth.…”

Section: Problem Statement and Preliminariesmentioning

confidence: 99%

“…Recently, autonomous marine vehicles have been greatly studied, which have been applied in different ocean engineering fields, such as seafloor mapping, maritime rescue, ocean sampling surveillance, and mine development and so forth 1‐17 . Therefore, many scholars have devoted themselves on the control problems of such systems 18‐25 . In this article, we will be devoted to the trajectory tracking control problem of such autonomous marine vehicles.…”

Section: Introductionmentioning

confidence: 99%

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Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Wang

Guo

et al. 2021

Intl J Robust & Nonlinear

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This article studies the neural‐network based backstepping control problem for autonomous marine vehicles perturbed by external disturbances. The actuator dead‐zone phenomenon, which is a common non‐smooth property caused by the complicated operating environment of autonomous marine vehicles, is also considered. To cope with the issue of “complexity explosion” and further decrease the tracking errors, a command filtering compensation strategy is also proposed, which guarantees satisfactory tracking performance and boundedness of the closed‐loop system signals. Finally, simulation studies are given to further demonstrate the effectiveness of the proposed control method.

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Section: Problem Statement and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Wang

Guo

et al. 2021

Intl J Robust & Nonlinear

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show abstract

“…Xia et al 21 proposed a fuzzy neural network robust adaptive control as the dead zone compensator for the input dead zone characteristics, which eliminates the adverse effects of dead zone characteristics on the system. Makavita et al 22 designed command governor adaptive control for the actuator dead zone of underwater drone measurement noise to improve system controllability and tracking performance. The use of the auxiliary task method by Ropars et al 23 adds additional constraints to the thrust distribution of horizontally redundant underwater vehicles in order to eliminate the effects of the dead zone of the thruster from the response.…”

Section: Introductionmentioning

confidence: 99%

“…The dead zone phenomenon is involved in the nonlinear characteristics of the actuators of underwater vehicles. [21][22][23] Failing to eliminate the influence of dead zone characteristics on the system may cause output error and may produce the limit cycle oscillations of the system, 24 which can reduce the control performance and even make the system unstable. Xia et al 21 proposed a fuzzy neural network robust adaptive control as the dead zone compensator for the input dead zone characteristics, which eliminates the adverse effects of dead zone characteristics on the system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy depth control with trajectory feedforward compensator for autonomous underwater vehicles

Chen

Wang

Chen

2019

Advances in Mechanical Engineering

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This article presents a computed-torque controller plus adaptive fuzzy trajectory feedforward compensator suitable for the trajectory tracking control of uncertain underwater vehicle. To address the issue of unavailable normalization factor, an adaptive fuzzy trajectory feedforward compensator is proposed and assembled at the input trajectory level of the computed-torque controller rather than at the joint drive torque position. The compensator serving as a low-pass filter is implemented outside the inner control loop by adjusting the desired characteristic depth. Due to the nearly unchanged internal control algorithm, the adaptive fuzzy compensator is feasible to implement and is robust when varying the feedback gain in the inner control loop. Moreover, an adaptive dead zone fuzzy compensator is designed to reduce the effect of the dead zone on the actuators of underwater vehicles according to the unknown input dead zone characteristics. To validate the effectiveness of the proposed controller, simulations are conducted for a desired characteristic depth, and the performance of the proposed controller has been compared with conventional controllers to illustrate the usefulness and efficiency of the proposed controller.

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Experimental Study of a Modified Command Governor Adaptive Controller for Depth Control of an Unmanned Underwater Vehicle

Makavita

Jayasinghe

Nguyen

et al. 2021

J. Marine. Sci. Appl.

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Command Governor Adaptive Control for Unmanned Underwater Vehicles with measurement noise and actuator dead-zone

Cited by 9 publications

References 8 publications

Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

Adaptive fuzzy depth control with trajectory feedforward compensator for autonomous underwater vehicles

Experimental Study of a Modified Command Governor Adaptive Controller for Depth Control of an Unmanned Underwater Vehicle

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