Skip to main content

Stable decentralized adaptive control design of robot manipulators using neural network approximations

Buy Article:

$55.00 plus tax (Refund Policy)

In this paper, we present a decentralized neural network (NN) adaptive technique for control of robot manipulators in the presence of unknown non-linear functions. Radial basis function NNs are used to approximate the non-linear functions to include the case of both parametric and dynamic uncertainty in each subsystem. The robustifying terms are added to the controllers to overcome the effects of the interconnections. The stability can be guaranteed by using a rigid proof. Finally, simulation is given to illustrate the effectiveness of the proposed algorithm.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Adaptive control; decentralized control; neural networks; radial basis function; system uncertainty.

Document Type: Regular Paper

Publication date: 2003-07-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect 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