Development of an Application for Controlling an Underwater Vehicle

Khutornaia, Ekaterina; Gnevashev, Yaroslav

doi:10.1016/j.trpro.2023.02.121

Cited by 3 publications

(2 citation statements)

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“…AUVs are becoming increasingly important in operations where equipment and divers have difficulties to complete, for example, dam detection [9], detection of wrecked ships or aircraft [10], undersea pipeline service [11], exploitation of submarine resources [12,13], submarine cable maintenance [14] and submarine three-dimensional terrain mapping [15], etc. For these reasons, AUVs have witnessed flourishing development in both military and civil fields [16,17]. However, the relatively small size, light weight, small inertia and vulnerability to external influence are all challenges to the maneuverability and motion control of AUVs.…”

Section: Introductionmentioning

confidence: 99%

A LSSVR Interactive Network for AUV Motion Control

Jiang

Wan

Zhang

et al. 2023

JMSE

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In view of the requirements on control precision of autonomous underwater vehicles (AUVs) in different operations, the improvement of AUV motion control accuracy is the focus of this paper. In regard to the unsatisfying robustness of traditional control methods, an interactive network based on Least Square Support Vector Regression (LSSVR) is therefore put forward. The network completed the identification of the strong nonlinear AUV dynamic characteristics based on the LSSVR theory and by virtue of the interactions between the offline and online modules, it achieved offline design and online optimization of the AUV control law. In addition to contrastive numerical simulations and sea trials with the classic S-plane method in AUV velocity and heading control, the LSSVR network was also tested in path following and long-range cruise. The precision and robustness and of the proposed network were verified by the high-accuracy control results of the aforesaid simulations and trials. The network can be of practical use in AUV control especially under unfamiliar water conditions with access to a limited number of control samples or little information of the operation site.

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Section: Introductionmentioning

confidence: 99%

A LSSVR Interactive Network for AUV Motion Control

Jiang

Wan

Zhang

et al. 2023

JMSE

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“…To some extent, the above control methods can meet the requirements of control accuracy and some have been applied in engineering practice. However, some of these methods are designed based on complex structures [33][34][35][36][37], some having multiple control parameters needing regulation [38][39][40] and some highly dependent on personal experience and field trials in parameter determination [41][42][43], which have restrained them from widespread use in practice. Moreover, the methods proposed in the existing studies are mostly verified in the simulation experiments instead of field trials.…”

Section: Introductionmentioning

confidence: 99%

Design and Verification of Deep Submergence Rescue Vehicle Motion Control System

Jiang,

Zhang,

Wan

et al. 2023

Sensors

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A six degree-of-freedom (DOF) motion control system for docking with a deep submergence rescue vehicle (DSRV) test platform was the focus of this study. The existing control methods can meet the general requirements of underwater operations, but the complex structures or multiple parameters of some methods have prevented them from widespread use. The majority of the existing methods assume the heeling effect to be negligible and ignore it, achieving motion control in only four or five DOFs. In view of the demanding requirements regarding positions and inclinations in six DOFs during the docking process, the software and hardware architectures of the DSRV platform were constructed, and then sparse filtering technology was introduced for data smoothing. Based on the adaptive control strategy and with a consideration of residual static loads, an improved S-plane control method was developed. By converting the force (moment) calculated by the controller to the body coordinate system, the complexity of thrust allocation was effectively reduced, and the challenge of thrust allocation in the case of a high inclination during dynamic positioning was solved accordingly. The automatic control of the trimming angle and heeling angle was realized with the linkage system of the ballast tank and pump valve. A PID method based on an intelligent integral was proposed, which not only dealt with the integral “saturation” problem, but also reduced the steady-state error and overshooting. Water pool experiments and sea trials were carried out in the presence of water currents for six-DOF motion control. The responsiveness and precision of the control system were verified by the pool experiment and sea trial results and could meet the control requirements in engineering practice. The reliability and operational stability of the proposed control system were also verified in a long-distance cruise.

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Research on the Influencing Factors of AUV Hovering Control in Null-Speed State

Wang,

Jiang,

Wan

et al. 2024

JMSE

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Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering control and determined injection and drainage functions based on optimal control theory. From analysis simulation experiments, the influence laws of control parameters, control timing and rate of injection and drainage control upon hovering control were deduced. It is proposed that, at the time of control parameter selection, the continuous injection and drainage rate at each time should be reduced as far as possible to relieve the demand on the volume of the reservoir when the requirement of depth control accuracy has been satisfied. In addition, the injection and drainage control should initiate when depth changes exceed 0.5 m. Suggestions are included on the minimum injection and drainage rate required for different initial disturbances. The proposed suggestions guide the design of hovering control systems and hovering control over intelligent underwater vehicles.

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Development of an Application for Controlling an Underwater Vehicle

Cited by 3 publications

References 0 publications

A LSSVR Interactive Network for AUV Motion Control

A LSSVR Interactive Network for AUV Motion Control

Design and Verification of Deep Submergence Rescue Vehicle Motion Control System

Research on the Influencing Factors of AUV Hovering Control in Null-Speed State

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