Author： Kiguchi Kazuo Fukuda Toshio
Publisher： Taylor & Francis Ltd
ISSN： 1568-5535
Source： Advanced Robotics, Vol.12, Iss.3, 1997-01, pp. : 191-208
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
_This paper presents an effective adaptive neural network feedback controller for force control of robot manipulators in an unknown environment by applying damping neurons which possess elastic-viscous properties. The unexpected overshooting and oscillation caused by the unknown and/or unmodeled dynamics of a robot manipulator and an environment can be decreased efficiently by the effect of the proposed damping neurons. Furthermore, a fuzzy controlled evaluation function is applied for the learning of the proposed neural network controller, so that the controller is able to adapt to the unknown environment more effectively. The effectiveness of the proposed neural network controller is evaluated by experiment with a 3 d.o.f. direct-drive planar robot manipulator.
Related content
Access to resources
Recommend
On rotations and translations with application to robot manipulators
Advanced Robotics, Vol. 8, Iss. 2, 1993-01 ,pp. :
By Zhang Yunong Cai Binghuang Zhang Lei Li Kene
Advanced Robotics, Vol. 22, Iss. 13-14, 2008-09 ,pp. :