Disturbance Observer-Based Model Predictive Visual Servo Control of Underwater Vehicles

Gao, Jian; Zhang, Guangjie; Wu, Puguo; Yan, Weisheng

doi:10.1109/oceanskobe.2018.8559214

Cited by 2 publications

(2 citation statements)

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“…A robust chattering-free sliding mode asymptotic tracking control design is presented for a fully actuated multirotor [10]. A disturbance observer-based model predictive controller is designed for image-based visual servoing of underwater vehicles subject to field-of view constraint, actuator saturation, and external disturbances [11]. An adaptive second-order fast nonsingular terminal sliding mode control scheme was addressed for the trajectory tracking of fully actuated autonomous underwater vehicles in the presence of dynamic uncertainties and time-varying external disturbances [12].…”

Section: Introductionmentioning

confidence: 99%

“…The proposed controller will involve real-time optimization to find a minimal-length path with respect to the metric (a geodesic) joining the current state to the desired state. But the existence of a flat metric usually simplifies the control problem [11], [15], [20], [32]. Hence, there is a growing need to extend existing methods or develop new ones for the purpose of applying contraction property on mechanical system.…”

Section: Introductionmentioning

confidence: 99%

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An Incremental Feedback Control for Uncertain Mechanical System

Guo

et al. 2020

IEEE Access

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This paper focuses on the tracking problem for fully-actuated mechanical systems with uncertain parameters and external disturbances. Based on the state feedback control of contraction analysis, the robust controller with extra gains is suggested to provide for the tracking of mechanical systems with uncertainties. The proposed control scheme can be redesigned with dual ideas and theoretically prove that the robust control renders uniform roundedness. Further more, the inertia matrices being uniformly bounded above are limited. The simulation is proposed to account for the effectiveness and robustness of the provided method. INDEX TERMS Increment, contraction analysis, fully-actuated system, robust control.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Incremental Feedback Control for Uncertain Mechanical System

Guo

et al. 2020

IEEE Access

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Neural network-based robust predictive control for visual servoing of autonomous vehicles with friction compensation

Lin,

Xing,

et al. 2024

Transactions of the Institute of Measurement and Control

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This paper proposes a neural network-based robust model predictive control (MPC) strategy for visual serving of autonomous vehicles (AVs) with uncertain payloads, ground friction disturbances, and air resistance effects. Based on the dynamics of visual servoing errors and driving of the AV, the quasi-min–max MPC is adopted to calculate the desired velocity of the AV subject to the constraints on the speed, control, and the visual field. The backpropagation (BP) neural network is then used to learn the ground friction disturbances of the AV, which is adopted to compensate the quasi-min–max MPC of the visual servoing system. Finally, the performance of the proposed controller is evaluated and verified by some comparison simulations.

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Disturbance Observer-Based Model Predictive Visual Servo Control of Underwater Vehicles

Cited by 2 publications

References 14 publications

An Incremental Feedback Control for Uncertain Mechanical System

An Incremental Feedback Control for Uncertain Mechanical System

Neural network-based robust predictive control for visual servoing of autonomous vehicles with friction compensation

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