Sliding mode adaptive neural network control for hybrid visual servoing of underwater vehicles

Gao, Jian; An, Xuman; Proctor, Alison A.; Bradley, Colin

doi:10.1016/j.oceaneng.2017.07.015

Cited by 54 publications

(15 citation statements)

References 32 publications

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“…Due to the approximation property of RBF neural network, there exits an ideal weighting matrix W * ∈ R 6×m , where m denotes the number of neurons in the hidden layer. W * satisfies W * ≤W withW > 0, such that [38,39]…”

Section: Region Tracking Control Designmentioning

confidence: 99%

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Observer Based Region Tracking Control for Underwater Vehicles Without Velocity Measurement

Liu

Zhang

Yao

et al. 2021

Preprint

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This paper addresses the problem of region tracking control for underwater vehicles without velocity measurement in marine environment. For this case, an improved region tracking control strategy is proposed based on a Nussbaum state observer. In the proposed method, a Nussbaum state observer is developed to estimate the unmeasured velocity of the vehicle. And then an improved region tracking control strategy is presented by incorporating the estimated results of the state observer, such that the tracking errors satisfy the requirement of the prescribed boundaries. In addition, a RBF neural network is applied to approximate the unknown dynamics of the vehicle. It is verified that the estimated error and the tracking error are uniformly ultimately bounded. Finally, the proposed observer-based region tracking control strategy is applied on an underwater vehicle to perform simulation studies and compared with a traditional backstepping controller and a traditional region tracking controller based on a high-gain observer. The comparative simulation results demonstrate the effectiveness of the proposed region tracking control strategy.

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Section: Region Tracking Control Designmentioning

confidence: 99%

“…In addition, the weighting matrixŴ and the parameterΞ are still from (38), and the estimated quantitiesx 1 andx 2 are from the observer (7).…”

Section: Simulation Verification For the Case Without Measurement Noisementioning

confidence: 99%

Observer Based Region Tracking Control for Underwater Vehicles Without Velocity Measurement

Liu

Zhang

Yao

et al. 2021

Preprint

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show abstract

“…When the target is blocked, our network also provides the controller with parameter changes. Gao's et al (2017) paper developed a sliding mode adaptive neural network control method based on dynamic inversion to track a hybrid visual servo reference trajectory generated from a constant target pose. Gao's et al (2015) paper proposed an adaptive neural network dynamic control based on the hierarchical model predictive image for the visual servoing (IBVS) of fully driven underwater vehicles.…”

Section: Introductionmentioning

confidence: 99%

Predictive visual control network for occlusion solution in human-following robot

Zou

2021

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Purpose The purpose of this paper is to propose a new video prediction-based methodology to solve the manufactural occlusion problem, which causes the loss of input images and uncertain controller parameters for the robot visual servo control. Design/methodology/approach This paper has put forward a method that can simultaneously generate images and controller parameter increments. Then, this paper also introduced target segmentation and designed a new comprehensive loss. Finally, this paper combines offline training to generate images and online training to generate controller parameter increments. Findings The data set experiments to prove that this method is better than the other four methods, and it can better restore the occluded situation of the human body in six manufactural scenarios. The simulation experiment proves that it can simultaneously generate image and controller parameter variations to improve the position accuracy of tracking under occlusions in manufacture. Originality/value The proposed method can effectively solve the occlusion problem in visual servo control.

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“…Visual servoing (VS) has attracted more and more attention of researchers from various fields of robots, such as manipulators (Cai et al, 2013(Cai et al, , 2016Li and Zhao, 2017), mobile robots (Ke et al, 2017;Wang et al, 2009;Zhang et al, 2018), quadrotors (Islam et al, 2015;Thomas et al, 2016) and underwater vehicles (Gao et al, 2015(Gao et al, , 2017. VS control may be divided into two types in the light of the feedback signals of the closed-loop system: (1) position-based visual servoing (PBVS) (Park et al, 2012;Thuilot et al, 2002); (2) imagebased visual servoing (IBVS) (Tahri et al, 2013;Xie et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Robust online model predictive control for image-based visual servoing in polar coordinates

Liu

Dong

2020

Transactions of the Institute of Measurement and Control

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In this paper, a novel robust online model predictive control (RMPC) method for image-based visual servoing (IBVS) in polar coordinates is proposed. First, the Jacobian matrix is transformed into a weighted combination of vertex matrices of convex polytopic by tensor product (TP) model transformation method. Then, a new IBVS control design condition for 6-DOF manipulator submitting to robot physical limitations and visibility constraints is obtained in polar coordinates by using RMPC technique. The optimal value of the control signal can be solved online when carrying out the convex optimization problem. The proposed control strategy can effectively improve the trajectory in the case that involves translation and rotation with fast response while averting the pseudo-inverse of the image Jacobian matrix. Conclusively, the effectiveness of the proposed scheme is validated by simulations and experiments on a 6-DOF manipulator.

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Sliding mode adaptive neural network control for hybrid visual servoing of underwater vehicles

Cited by 54 publications

References 32 publications

Observer Based Region Tracking Control for Underwater Vehicles Without Velocity Measurement

Observer Based Region Tracking Control for Underwater Vehicles Without Velocity Measurement

Predictive visual control network for occlusion solution in human-following robot

Robust online model predictive control for image-based visual servoing in polar coordinates

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