Robust adaptive visual tracking control for uncertain robotic systems with unknown dead-zone inputs

Wang, Fujie; Li, Zhi; Chen, C.L. Philip; Zhang, Yun

doi:10.1016/j.jfranklin.2019.05.040

Cited by 16 publications

(10 citation statements)

References 37 publications

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“…We define the nonlinear model for the robots with n degrees of freedom in the joint space as [1], [2], [4]:…”

Section: Some Properties Of Robotsmentioning

confidence: 99%

“…We represent the actuators nonlinearities e as [1]- [4]: n r , n l , w r and w l as constant terms for the actuators nonlinearities. Note that v is the input of the actuators nonlinearities.…”

Section: Some Properties Of Robotsmentioning

confidence: 99%

“…The nonlinear uncertainties and external perturbations are unwanted characteristics in nonlinear models because they can severely limit their performance or damage their components; this fact has been drawing much interest in the community for a long time [1]- [4]. The linear quadratic regulator is one approach used to reach constant paths in linear models, it is called optimization [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

“…Actuators nonlinearities are a kind of external perturbations in the robots nonlinear models yielded by the interaction of actuators with the environment [1]- [4]. This research is focused on the stabilization of robots subject to actuators nonlinearities with a regulator containing the sigmoid mapping.…”

Section: Introductionmentioning

confidence: 99%

“…= 0, and it is (13). Remark 3: Our regulator (12) requires to comply with conditions (11), (7) to be applied for the stabilization of robots (3), (4).…”

mentioning

confidence: 99%

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Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

et al. 2020

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Actuators nonlinearities are unknown external perturbations in robots, which are unwanted because they can severely limit their performance. This research is focused on the stabilization of robots subject to actuators nonlinearities with a regulator containing the sigmoid mapping. Our regulator has the following three main characteristics: a) a sigmoid mapping is used to ensure boundedness of the regulator law terms, b) the chattering is reduced by the usage of the saturation mapping instead of the signum mapping, and c) the stabilization is ensured by the Lyapunov analysis. Finally, we evaluate our regulator for the stabilization of two robots.

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“…We define the nonlinear model for the robots with n degrees of freedom in the joint space as [1], [2], [4]:…”

Section: Some Properties Of Robotsmentioning

confidence: 99%

Section: Some Properties Of Robotsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…= 0, and it is (13). Remark 3: Our regulator (12) requires to comply with conditions (11), (7) to be applied for the stabilization of robots (3), (4).…”

mentioning

confidence: 99%

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Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

et al. 2020

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Adaptive tracking control of robot manipulators with input saturation and time‐varying output constraints

Huang

Wang

et al. 2020

Asian Journal of Control

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This paper investigates adaptive tracking control in task space for robot manipulators with uncertain system dynamics, input saturation, and time‐varying output constraints simultaneously. An auxiliary system is constructed to compensate the effect of the input saturation, and an asymmetric barrier Lyapunov function (BLF) is applied to tackle time‐varying output constraints, while radial basis function (RBF) neural networks (NN) are used to approximate the unknown closed‐loop dynamics. By introducing a disturbance observer (DO), unknown external disturbances from humans and environment are estimated, and NN approximation errors are compensated. A novel adaptive NN tracking controller is designed to guarantee all signals in the closed‐loop system are semi‐globally uniformly ultimately bounded (UUB), while the tracking errors and observer errors converge to a small neighborhood of zero, and the time‐varying output constraints are not violated. Moreover, the adaptive tracking control of redundant robot manipulators is studied, and the subtask and task space tracking of redundant robot manipulators are realized simultaneously, while the stability of the system is proved by Lyapunov stability theory. Finally, some simulation results are presented to verify the effectiveness and superiority of the proposed control scheme.

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Homography‐based uncalibrated visual servoing with neural‐network‐assisted robust filtering scheme and adaptive servo gain

Wang

et al. 2022

Asian Journal of Control

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In this paper, a homography‐based uncalibrated visual servo system with neural‐network‐assisted robust filtering scheme and adaptive servo gain is presented. This system employs a homography‐based task function which is robust to image defects. A neural‐network‐assisted robust filtering method which combines the new form of smooth variable structure filter (SVSF) with a radial basis function (RBF) neural network is proposed to estimate the total Jacobian between task function and robot joints. The RBF neural network in this filtering method plays the role as a corrector to further improve the accuracy and compensate the interference caused by the measurement errors of image features. The controller that directly controls the robot joints based on the estimated total Jacobian is designed for achieving the robustness to robot parameters errors. By adopting this filtering scheme, the visual servo system shows better accuracy and convincing anti‐interference ability. In addition, a novel Q‐learning strategy is introduced for this homography‐based system to make adaptive adjustment for the servo gain. This adaptive gain enables the system to achieve a faster convergence speed while ensuring the accuracy. Several simulations and experiments have been carried out to verify the performance of the proposed system.

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Robust adaptive visual tracking control for uncertain robotic systems with unknown dead-zone inputs

Cited by 16 publications

References 37 publications

Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

Adaptive tracking control of robot manipulators with input saturation and time‐varying output constraints

Homography‐based uncalibrated visual servoing with neural‐network‐assisted robust filtering scheme and adaptive servo gain

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