Title :
Impedance control of robot manipulator using artificial intelligence
Author :
Kim, Han Me ; Chang Don Lee ; Kim, Doo Hyeong ; Park, Kyoung Taik
Author_Institution :
Environ. & Energy Syst. Res. Div., KIMM, Daejeon, South Korea
Abstract :
This paper deals with a sliding mode impedance control (SMIC) of end-effector of robot manipulator using a tracking control scheme and a real-time artificial intelligence algorithm based on a radial basis function neural networks(RBFNNs). To real-time estimate the design parameters of desired impedance model such as desired inertia, damping, and stiffness desired impedance, SMIC(sliding mode impedance control) with RBFNNs algorithm is proposed.
Keywords :
electric variables control; end effectors; radial basis function networks; variable structure systems; artificial intelligence; radial basis function neural networks; robot manipulator end effector; sliding mode impedance control; tracking control scheme; Algorithm design and analysis; Artificial neural networks; Impedance; Manipulator dynamics; Robustness; Impedance control; radial basis function neural networks; sliding mode control;
Conference_Titel :
Control Automation and Systems (ICCAS), 2010 International Conference on
Conference_Location :
Gyeonggi-do
Print_ISBN :
978-1-4244-7453-0
Electronic_ISBN :
978-89-93215-02-1
