Neural network controllers for robot manipulators application of damping neurons

$61.74 plus tax (Refund Policy)

Buy Article:

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.

Document Type: Research Article

DOI: http://dx.doi.org/10.1163/156855398X00145

Affiliations: 1: Department of Industrial and Systems Engineering, Niigata College of Technology 5-13-7 Kamishin 'eicho, Niigata-shi, Niigata 950-21, Japan 2: Center for Cooperative Research in Advanced Science and Technology Nagoya University l Furo-cho, Chikusa-ku, Nagoya 464-01, Japan

Publication date: January 1, 1997

Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more