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New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion (2019)
Journal Article
Wei, L., Jin, L., Yang, C., Chen, K., & Li, W. (2021). New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(4), 2611 - 2623. https://doi.org/10.1109/TSMC.2019.2916892

Nonlinear optimization problems with dynamical parameters are widely arising in many practical scientific and engineering applications, and various computational models are presented for solving them under the hypothesis of short-time invariance. To... Read More about New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion.

Composite learning adaptive backstepping control using neural networks with compact supports (2019)
Journal Article
Pan, Y., Yang, C., Pratama, M., & Yu, H. (2019). Composite learning adaptive backstepping control using neural networks with compact supports. International Journal of Adaptive Control and Signal Processing, 33(12), 1726-1738. https://doi.org/10.1002/acs.3002

© 2019 John Wiley & Sons, Ltd. The ability to learn is crucial for neural network (NN) control as it is able to enhance the overall stability and robustness of control systems. In this study, a composite learning control strategy is proposed for a... Read More about Composite learning adaptive backstepping control using neural networks with compact supports.

Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results (2019)
Journal Article
Chen, L., Cui, R., Yang, C., & Yan, W. (2020). Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results. IEEE Transactions on Industrial Electronics, 67(5), 4024-4035. https://doi.org/10.1109/TIE.2019.2914631

In this paper, an adaptive trajectory tracking control algorithm for underactuated unmanned surface vessels (USVs) with guaranteed transient performance is proposed. To meet the realistic dynamical model of USVs, we consider that the mass and dam... Read More about Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results.

Force Sensorless Admittance Control with Neural Learning for Robots with Actuator Saturation (2019)
Journal Article
Peng, G., Yang, C., He, W., & Chen, C. L. (2020). Force Sensorless Admittance Control with Neural Learning for Robots with Actuator Saturation. IEEE Transactions on Industrial Electronics, 67(4), 3138-3148. https://doi.org/10.1109/TIE.2019.2912781

© 1982-2012 IEEE. In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment is defined as linear models with unknow... Read More about Force Sensorless Admittance Control with Neural Learning for Robots with Actuator Saturation.

Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback (2019)
Journal Article
Kong, L., He, W., Dong, Y., Cheng, L., Yang, C., & Li, Z. (2021). Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(3), 1735-1746. https://doi.org/10.1109/TSMC.2019.2901277

In this paper, an adaptive neural bounded control scheme is proposed for an n-link rigid robotic manipulator with unknown dynamics. With the combination of the neural approximation and backstepping technique, an adaptive neural network control policy... Read More about Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback.

A task learning mechanism for the telerobots (2019)
Journal Article
Luo, J., Yang, C., Li, Q., & Wang, M. (2019). A task learning mechanism for the telerobots. International Journal of Humanoid Robotics, 16(2), 1950009. https://doi.org/10.1142/S0219843619500099

Telerobotic systems have attracted growing attention because of their superiority in the dangerous or unknown interaction tasks. It is very challengeable to exploit such systems to implement complex tasks in an autonomous way. In this paper, we propo... Read More about A task learning mechanism for the telerobots.

Efficient 3D object recognition via geometric information preservation (2019)
Journal Article
Liu, H., Cong, Y., Yang, C., & Tang, Y. (2019). Efficient 3D object recognition via geometric information preservation. Pattern Recognition, 92, 135-145. https://doi.org/10.1016/j.patcog.2019.03.025

© 2019 Elsevier Ltd Accurate 3D object recognition and 6-DOF pose estimation have been pervasively applied to a variety of applications, such as unmanned warehouse, cooperative robots, and manufacturing industry. How to extract a robust and represent... Read More about Efficient 3D object recognition via geometric information preservation.

Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning (2019)
Journal Article
Kong, L., He, W., Yang, C., Li, Z., & Sun, C. (2019). Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning. IEEE Transactions on Cybernetics, 49(8), 3052-3063. https://doi.org/10.1109/TCYB.2018.2838573

In this paper, we investigate fuzzy neural network (FNN) control using impedance learning for coordinated multiple constrained robots carrying a common object in the presence of the unknown robotic dynamics and the unknown environment with which the... Read More about Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning.

Admittance-based adaptive cooperative control for multiple manipulators with output constraints (2019)
Journal Article
Li, Y., Yang, C., Yan, W., Cui, R., & Annamalai, A. (2019). Admittance-based adaptive cooperative control for multiple manipulators with output constraints. IEEE Transactions on Neural Networks and Learning Systems, 30(12), 3621-3632. https://doi.org/10.1109/TNNLS.2019.2897847

This paper proposes a novel adaptive control methodology based on the admittance model for multiple manipulators transporting a rigid object cooperatively along a predefined desired trajectory. First, an admittance model is creatively applied to gene... Read More about Admittance-based adaptive cooperative control for multiple manipulators with output constraints.

Adaptive fuzzy Gaussian mixture models for shape approximation in Robot Grasping (2019)
Journal Article
Lin, H., Zhang, T., Chen, Z., Song, H., & Yang, C. (2019). Adaptive fuzzy Gaussian mixture models for shape approximation in Robot Grasping. International Journal of Fuzzy Systems, 21(4), 1026-1037. https://doi.org/10.1007/s40815-018-00604-8

Robotic grasping has always been a challenging task for both service and industrial robots. The ability of grasp planning for novel objects is necessary for a robot to autonomously perform grasps under unknown environments. In this work, we consider... Read More about Adaptive fuzzy Gaussian mixture models for shape approximation in Robot Grasping.

Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery (2019)
Journal Article
Su, H., Yang, C., Ferrigno, G., & De Momi, E. (2019). Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery. IEEE Robotics and Automation Letters, 4(2), 1447-1453. https://doi.org/10.1109/LRA.2019.2897145

© 2016 IEEE. An improved human-robot collaborative control scheme is proposed in a teleoperated minimally invasive surgery scenario, based on a hierarchical operational space formulation of a seven-degree-of-freedom redundant robot. Redundancy is exp... Read More about Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery.

An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions (2019)
Journal Article
Xia, J., Zhang, Y., Yang, C., Wang, M., & Annamalai, A. (2019). An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions. International Journal of Systems Science, 50(3), 638-651. https://doi.org/10.1080/00207721.2019.1567863

Conventional Neural Network (NN) control for robots uses radial basis function (RBF) and for n-link robot with online control, the number of nodes and weighting matrix increases exponentially, which requires a number of calculations to be performed w... Read More about An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions.

Enhanced teleoperation performance using hybrid control and virtual fixture (2019)
Journal Article
Luo, J., Yang, C., Wang, N., & Wang, M. (2019). Enhanced teleoperation performance using hybrid control and virtual fixture. International Journal of Systems Science, 50(3), 451-462. https://doi.org/10.1080/00207721.2018.1562128

To develop secure, natural and effective teleoperation, the perception of the slave plays a key role for the interaction of a human operator with the environment. By sensing slave information, the human operator can choose the correct operation in a... Read More about Enhanced teleoperation performance using hybrid control and virtual fixture.

Head-raising of snake robots based on a predefined spiral curve method (2018)
Journal Article
Zhang, X., Liu, J., Ju, Z., & Yang, C. (2018). Head-raising of snake robots based on a predefined spiral curve method. Applied Sciences, 8(11), 2011. https://doi.org/10.3390/app8112011

© 2018 by the authors. A snake robot has to raise its head to acquire a wide visual space for planning complex tasks such as inspecting unknown environments, tracking a flying object and acting as a manipulator with its raising part. However, only a... Read More about Head-raising of snake robots based on a predefined spiral curve method.