By Topic

Adaptive high precision position control for a flexible joint with friction and parameter uncertainties using neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Sidi, E.Y.O. ; Dept. de Genie Electr., Quebec Univ., Trois-Rivieres, Que., Canada ; Sicard, P. ; Massicotte, D. ; Lesueur, S.

Dynamic position-control of a flexible joint is proposed by applying adaptive control and artificial neural networks (ANNs). A flexible joint is modeled, including Coulomb and static frictions and the model is represented as an ANN. The control strategy is based on a dual loop strategy. An outer load state feedback is used to compute desired load torque and motor state. An inner motor state feedback loop is used to control the motor. Both loops use feedforward compensation of friction. The controllers are represented as an ANN, the system parameters being the weights of the output layer. Parameter identification is achieved using the recursive least squares algorithm. Simulation results show that the proposed controller can suppress vibrations

Published in:

Electrical and Computer Engineering, 1998. IEEE Canadian Conference on  (Volume:1 )

Date of Conference:

24-28 May 1998