Trajectory Tracking Control of Robotic Manipulators by Multi-layer Neural Networks

2020 ◽  
Author(s):  
Ganggang Zhong ◽  
Yanan Li ◽  
Jiangang Li
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Robotic Manipulators ◽  
Trajectory Tracking Control

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

scholarly journals INTEGRAL SLIDING MODE CONTROL FOR TRAJECTORY TRACKING CONTROL OF ROBOTIC MANIPULATORS USING AN ADAPTIVE TWISTING ALGORITHM

2019 ◽  
Vol 17 (12.2) ◽  
pp. 42
Author(s):  
Anh Tuan Vo ◽  
Ngoc Hoai An Nguyen ◽  
Duy Duong Pham
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Trajectory Tracking Control ◽  
Integral Sliding Mode Control ◽  
Integral Sliding Mode ◽  
Mode Control

This paper proposes an integral sliding mode for trajectory tracking control of robotic manipulators. Our proposed control method is developed on the foundation of the benefits in both integral sliding mode control and adaptive twisting control algorithm, such as high robustness, high accuracy, estimation ability, and chattering elimination. In this paper, the proposed integral sliding mode controller is designed with the elimination of the reaching phase to offer better trajectory tracking precision and to stabilize the robot system. To reduce the calculation burden along with chattering rejection, an adaptive twisting controller with only one simple adaptive rule is employed to estimate the upper-boundary values of the lumped uncertainties. Accordingly, the requirement of their prior knowledge is removed and then decrease the computation complexity. Consequently, this control method provides better trajectory tracking accuracy to handle the dynamic uncertainties and external disturbances more strongly. The system global stability of the control system is guaranteed by using Lyapunov criteria. Finally, simulated examples are performed to analyze the effectiveness of our control approach for position pathway tracking control of a 2-DOF parallel manipulator.

Sign in / Sign up

Export Citation Format

Share Document