Rotation tracking control strategy of underwater flexible telescopic manipulator based on neural network compensation for water environment disturbance

Shang, Dongyang; Li, Xiaopeng; Yin, Meng; Zhou, Shuai

doi:10.1016/j.oceaneng.2023.115245

Cited by 7 publications

(2 citation statements)

References 38 publications

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“…When the fluid is water, flexible components in propellers and underwater robotics adapt to fluid dynamics, improving maneuverability, and efficiency. Shang et al [80] developed an underwater flexible telescopic manipulator, the flexibility of which enables it to handle dynamic underwater currents and obstacles in challenging tasks such as deep-sea exploration and resource extraction [see Fig. 1(e)].…”

Section: F In-fluid Turbine Designmentioning

confidence: 99%

Advances in Flexible Robotic Manipulator Systems — Part II: Planning, Control, Applications, and Perspectives

Li,

Gao

et al. 2024

IEEE/ASME Trans. Mechatron.

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This work offers a review of techniques related to flexible robotic manipulator (FRM) systems. Our review is divided into two parts. The first part presents the background of FRMs, a survey of previous surveys, and FRM dynamic modeling methods. This article is the second part, which reviews the advances in FRM motion planners and controllers, along with the emerging applications and perspectives. Compared with previous FRM surveys, our work presents a more detailed categorization and extensive review of emerging research trends since 2020. The ongoing development of FRMs is marking advancements in the field of robotics.

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Section: F In-fluid Turbine Designmentioning

confidence: 99%

Advances in Flexible Robotic Manipulator Systems — Part II: Planning, Control, Applications, and Perspectives

Li,

Gao

et al. 2024

IEEE/ASME Trans. Mechatron.

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“…A comprehensive framework based on PID and fuzzy logic control methods has been proposed for the control of an underwater robot manipulator system (UVMS) [8]. An adaptive controller based on neural network has been proposed, in which the neural network is used to compensate the underwater disturbance torque to improve the robustness of the manipulator control system [9]. An adaptive controller based on observer compensation has been proposed, in which the observer is used to estimate the friction torque of the joint and compensate the controller [10].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression

Liu,

Xu,

et al. 2023

JMSE

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In this paper, the precise control of the underwater manipulator has studied under the conditions of uncertain underwater dynamics and time-varying external interference. An improved adaptive model predictive control (MPC) method is proposed for a multiple-degrees-of-freedom (DOF) underwater manipulator. In this method, the Gaussian process regression (GPR) algorithm has been embedded into the precise trajectory tracking control of the underwater manipulator. The GPR algorithm has been used to predict the water resistance, additional mass, buoyancy and external interference in real time, and the control law has been calculated by the terminal constraint MPC to realize the adaptive internal and external interference compensation. In addition, a more accurate dynamic model of the underwater 6-DOF manipulator is established by combining Lagrange equation with Morrison formula. Finally, the effectiveness of the adaptive MPC using GPR method is verified by a series of comparative simulations.

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Combined vibration control of flexible cantilever beam driven by MFC actuators and rotary motor

Lyu,

Li,

Jia

2024

Acta Mech

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Rotation tracking control strategy of underwater flexible telescopic manipulator based on neural network compensation for water environment disturbance

Cited by 7 publications

References 38 publications

Advances in Flexible Robotic Manipulator Systems — Part II: Planning, Control, Applications, and Perspectives

Advances in Flexible Robotic Manipulator Systems — Part II: Planning, Control, Applications, and Perspectives

Adaptive Model Predictive Control for Underwater Manipulators Using Gaussian Process Regression

Combined vibration control of flexible cantilever beam driven by MFC actuators and rotary motor

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