scholarly journals Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

2017 ◽  
Vol 12 (3) ◽  
pp. 1271-1279 ◽  
Author(s):  
Hyo-Jeong Bae ◽  
Maolin Jin ◽  
Jinho Suh ◽  
Jun Young Lee ◽  
Pyung-Hun Chang ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Robot Manipulators ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Fuzzy Logic Systems ◽  
Logic Systems

scholarly journals Task Space Trajectory Tracking Control of Robot Manipulators with Uncertain Kinematics and Dynamics

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Xichang Liang ◽  
Yi Wan ◽  
Chengrui Zhang
Keyword(s):  
Time Delay ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Kinematics And Dynamics ◽  
Task Space ◽  
Terminal Sliding Mode ◽  
Nonsingular Terminal Sliding Mode

To improve the tracking precision of robot manipulators’ end-effector with uncertain kinematics and dynamics in the task space, a new control method is proposed. The controller is based on time delay estimation and combines with the nonsingular terminal sliding mode (NTSM) and adaptive fuzzy logic control scheme. Kinematic parameters are not exactly required with the consideration of kinematic uncertainties in the controller. No dynamic models or numerous parameters of the robot manipulator system are required with the use of TDE. Thus, the controller is simple structure and suitable for practical applications. Furthermore, errors caused by time delay estimation are compensated by the adaptive fuzzy nonsingular terminal sliding mode scheme. The simulation is performed on a 2-DOF robot manipulator with three cases in the task space. The results show that the proposed controller provides faster convergence rate and higher tracking precision than TDE based NTSM and improved TDE based NTSM controller.

Decentralized fuzzy linguistic control of multiple robotic manipulators with guaranteed global stability

2019 ◽  
Vol 20 (1) ◽  
pp. 185-204
Author(s):  
Yongqing Fan ◽  
Wenqing Wang ◽  
Xiangkui Jiang ◽  
Zhen Li
Keyword(s):  
Fuzzy Logic ◽  
Global Stability ◽  
Fuzzy Controller ◽  
Robot Manipulators ◽  
Design Method ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Fuzzy Logic Systems ◽  
Approximation Accuracy ◽  
Logic Systems

Abstract A decentralized adaptive control based on human linguistic is investigated to learn human behaviors for multiple robotic manipulators. Many experts’ words or sentences can be transferred into the control actions by employing membership functions in robot systems, which can be synthesized fuzzy controller by employing reasoning mechanism. For the unknown model dynamical robot manipulators, one adjustable parameter that relates to the approximation accuracy of fuzzy logic systems is introduced at first, which be utilized to deal with the unknown dynamics of robot manipulators. Switching fuzzy adaptive controller is designed to overcome the limitation of logic structure that the number of adaptive laws only focus on fuzzy rules in conventional fuzzy logic systems. Another advantage of this design method is that the control with human linguistic extend the semi-global stability to global stability. Finally, effectiveness of the developed control design scheme has been shown in simulation example.

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