The Trajectory Tracking Control of 2-Link Flexible Arm Using Tendon Mechanism

1995 ◽  
Author(s):  
Hui Cao ◽  
Kazuo Yoshida
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Equations Of Motion ◽  
Real Time Control ◽  
Trajectory Tracking Control ◽  
Modeling And Control ◽  
Time Control ◽  
Flexible Arm ◽  
Resolved Acceleration Control

Abstract This paper deals with the trajectory tracking control of a 2-link flexible arm using tendon control mechanism. The purpose of this research is to establish modeling and control method for flexible arm. First, the equations of kinematic relationship and equations of motion are derived by using static deflection curve. From these equations, the relationship between tip trajectory and joint input torque is established. Second, a trajectory tracking controller is designed for real-time control of the flexible arm by using the resolved acceleration control method. Then the controller is carried out to track the designed straight line and circular trajectory. The simulation results show the effectiveness of the proposed method. To summarize these results, it was demonstrated that the tendon mechanism can be used to solve the tracking problem of the flexible arms and it also has a higher tracking precision than traditional method.

scholarly journals A Neural Network Based Dynamic Control Method for Soft Pneumatic Actuator with Symmetrical Chambers

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 112
Author(s):  
Yiqing Li ◽  
Yan Cao ◽  
Feng Jia
Keyword(s):  
Neural Network ◽  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Dynamic Control ◽  
The State ◽  
Pneumatic Actuator ◽  
Trajectory Tracking Control ◽  
Modeling And Control

Dynamic modeling and control of the soft pneumatic actuators are challenging research. In this paper, a neural network based dynamic control method used for a soft pneumatic actuator with symmetrical chambers is proposed. The neural network is introduced to create the dynamic model for predicting the state of the actuator. In this dynamic model, the effect of the uninflated rubber block on bending deformation is considered. Both pressures of the actuator are used for predicting the state of the actuator during the bending motion. The controller is designed based on this dynamic model for trajectory tracking control. Three types of trajectory tracking control experiments are performed to validate the proposed method. The results show that the proposed control method can control the motion of the actuator and track the trajectory effectively.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

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.

Fixed-time trajectory tracking control for multiple nonholonomic mobile robots

2020 ◽  
pp. 014233122096641
Author(s):  
Meiying Ou ◽  
Haibin Sun ◽  
Zhenxing Zhang ◽  
Lingchun Li
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Initial Conditions ◽  
Fixed Time ◽  
Nonholonomic Mobile Robots ◽  
Trajectory Tracking Control ◽  
Adding A Power Integrator ◽  
Time Control ◽  
Power Integrator

This paper investigates the fixed-time trajectory tracking control for a group of nonholonomic mobile robots, where the desired trajectory is generated by a virtual leader, the leader’s information is available to only a subset of the followers, and the followers are assumed to have only local interaction. According to fixed-time control theory and adding a power integrator technique, distributed fixed-time tracking controllers are developed for each robot such that all states of each robot can reach the desired value in a fixed time. Moreover, the settling time is independent of the system initial conditions and only determined by the controller parameters. Simulation results illustrate and verify the effectiveness of the proposed schemes.

Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot

2020 ◽  
Vol 101 (1) ◽  
pp. 233-253
Author(s):  
Jianqing Peng ◽  
Wenfu Xu ◽  
Taiwei Yang ◽  
Zhonghua Hu ◽  
Bin Liang
Keyword(s):  
Dynamic Modeling ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Redundant Robot

Group Control of Mobile Robots for More Efficient Searches – Verification of Semi-Autonomous Trajectory Tracking Motions in Irregular Ground Environment –

2018 ◽  
Vol 30 (6) ◽  
pp. 980-990
Author(s):  
Yoshikazu Ohtsubo ◽  
Morihito Matsuyama ◽  
◽  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Potential Method ◽  
Gravity Potential ◽  
Trajectory Tracking Control ◽  
Robot Operating System ◽  
Uneven Terrain ◽  
Disaster Area ◽  
Autonomous Search

After the occurrence of a disaster, it is critical to perform rapid and accurate searching operations in the large disaster area. It is efficient to perform such operations using multiple mobile exploration robots. Accordingly, we focus on cooperative cruising in a disaster environment and propose the trajectory tracking control method for a semi-autonomous search robot. We apply a robot operating system (ROS) to execute the trajectory tracking control using two mobile exploration robots. In this paper, we describe the trajectory tracking control using gravity potential method and the results of a cooperative cruising experiment in an uneven terrain environment.

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