Force/Position Hybrid Control for a Hexa Robot Using Gradient Descent Iterative Learning Control Algorithm

This paper presents an approach of the force/position hybrid control for a hexa parallel robot to guarantee a safe and accurate interaction when touching the object surface. A double-loop PID controller is proposed to replace the common PID controller in the position control to eliminate position er...

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Veröffentlicht in:IEEE access Jg. 7; S. 72329 - 72342
Hauptverfasser: Huynh, Ba-Phuc, Wu, Cheng-Wei, Kuo, Yong-Lin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Control algorithms
Control theory
Controllers
double-loop PID
Hexa robot
Hybrid control
Impedance
impedance control
iterative learning
Iterative methods
Kinematics
Machine learning
Manipulators
Mathematical models
Mechanical systems
Parallel robots
Parameter estimation
Parameter modification
Position control
Position errors
Proportional integral derivative
Robot control
Robot kinematics
Robots
Unknown environments
ISSN:2169-3536, 2169-3536
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Zusammenfassung:This paper presents an approach of the force/position hybrid control for a hexa parallel robot to guarantee a safe and accurate interaction when touching the object surface. A double-loop PID controller is proposed to replace the common PID controller in the position control to eliminate position errors due to the dynamics coupling effect between the arms and the vibration of the mechanical system. An impedance control model is used to guarantee a safe and accurate interaction when touching the object surface. In addition, a gradient descent iterative learning control algorithm is used and modified to determine the optimal impedance parameters in unknown environments. A model of the robot is built in SimMechanics to simulate and estimate system parameters. After that, the experimental work was conducted on a real robot to verify the effectiveness and feasibility of the proposed method.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2920020