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

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

Ba-Phuc Huynh, Chengwei Wu, Yong-Lin Kuo

Year
2019
Citations
32
Access
Open access

Abstract

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.

Keywords

Gradient descentIterative learning controlPID controllerControl theory (sociology)Computer sciencePosition (finance)Controller (irrigation)RobotImpedance controlCoupling (piping)

Related papers

Browse all OTHER papers