A new terminal converging adaptive control for 6-degree-of-freedom parallel robotic manipulators with bounded control inputs

Zhao, Ding; Spurgeon, Sarah K.; Liang, Hao; Li, Shaoyuan; Zhu, Quanmin

doi:10.1177/0959651817698333

Cited by 2 publications

(3 citation statements)

References 26 publications

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“…The Lyapunov stability criteria 30,31 is employed to verify the closed-loop stability of the compliant gripper system under NNSMC control strategy. A positive-definite Lyapunov function candidate is adopted as follow…”

Section: Modeling and Control Of Compliant Grippermentioning

confidence: 99%

“…The perturbation estimation and the neural network can be implemented via the control module of the RTW environment, which helps to reduce the computation burden of the developed NNSMC strategy. The Lyapunov stability criteria 30,31 is employed to verify the closed-loop stability of the compliant gripper system under NNSMC control strategy. A positivedefinite Lyapunov function candidate is adopted as follow…”

Section: Nnsmc Position-controller Designmentioning

confidence: 99%

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Neural network–based sliding-mode control of a tendon sheath–actuated compliant rescue manipulator

Wang

Chen

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part I:

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The novel contribution of this article is to propose a neural network–based sliding-mode control strategy for improving the position-control performance of a tendon sheath–actuated compliant rescue manipulator. Structural design of a rescue robot with slender and compliant mechanical structure is introduced. The developed robot is capable of drilling into the narrow space under debris and accommodating complicated configuration in ruins. Dynamics modeling and parameters identification of a compliant gripper with flexible tendon sheath transmission are researched and discussed. Moreover, the neural network–based sliding-mode control scheme developed based on radial basis function network is proposed to improve the position-control accuracy of the gripper with modeling uncertainties and external disturbances. The stability of the proposed control system is demonstrated using Lyapunov stability theory. Further experimental investigation including trajectory-tracking experiments and step-response experiments are conducted to confirm the effectiveness of the proposed neural network–based sliding-mode control scheme. Experimental results show that the proposed neural network–based sliding-mode control scheme is superior to cascaded proportional–integral–derivative controller and conventional sliding-mode controller in position-control application.

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Section: Modeling and Control Of Compliant Grippermentioning

confidence: 99%

Section: Nnsmc Position-controller Designmentioning

confidence: 99%

Neural network–based sliding-mode control of a tendon sheath–actuated compliant rescue manipulator

Wang

Chen

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…The control method for parallel robots can be classified into two categories: one is kinematic control methods based on the kinematic model of robots, 14,15 the other is dynamic control methods based on the rigid body dynamic model of robots. 16,17 Usually, kinematic control methods ignore the dynamic charactsristic of robots; thus, its control algorithm is simple, which is more suitable for a real robot system. Ruiz-Hidalgo et al 18 proposed a proportional-integral-derivative (PID) controller with tracking for a new configuration of a 3-DOF parallel robot, which can asymptotically track a desired reference trajectory.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking control of delta parallel robot based on disturbance observer

Mei

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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Delta parallel robot is widely used in the manufacturing process of food, medicine, electronics and military industries, which is a highly nonlinear system with strongly uncertain dynamics. Therefore, there are many difficulties in the controller design of delta robot. Based on the simplified dynamic model, a nonlinear PD+ controller with nonlinear disturbance observer is proposed for Delta parallel robot in this article, which can realize high-precision trajectory tracking in high-speed and high-acceleration motion. Then, the asymptotic stability of the closed-loop system’s equilibrium point is proven by utilizing Lyapunov techniques and LaSalle’s invariance theorem. It is obvious that the proposed controller is significantly less dependent on the accuracy of the dynamic model. Besides, a disturbance observer based on the generalized momentum is constructed, which can effectively observe and compensate the disturbances. What’s more, the constructed disturbance observer avoids the calculation of the inverse of inertia matrix, which will greatly improve the response speed of the controller. The simulation results show that the proposed controller can assure better trajectory tracking accuracy in high-speed and high-acceleration motion. And the disturbance observer can effectively estimate the disturbance. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:This work was supported by the National Natural Science Foundation of China (grant number51474320).

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A new terminal converging adaptive control for 6-degree-of-freedom parallel robotic manipulators with bounded control inputs

Cited by 2 publications

References 26 publications

Neural network–based sliding-mode control of a tendon sheath–actuated compliant rescue manipulator

Neural network–based sliding-mode control of a tendon sheath–actuated compliant rescue manipulator

Trajectory tracking control of delta parallel robot based on disturbance observer

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