By Topic

Neural network adaptive sliding mode control and its application to SCARA type robot manipulator

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

2 Author(s)
Ertugrul, M. ; Robotics & Autom. Group, Tubitak Marmara Res. Center, Gebze, Turkey ; Kaynak, Okyay

A synergistic combination of neural networks with sliding mode control is proposed. As a result, the chattering is eliminated and error performance of SMC is improved. In such an approach, the determination of the structure of NN, i.e. number of layers, number of neurons at each layer, etc. does not come up as a problem because these are directly related to the SMC. A Lyapunov function is selected for the design of the SMC and gradient descent is used for weight adaptation of the neural network. The criterion that is minimized for gain adaptation is selected as the sum of the squares of the control signal and the sliding function. This novel approach is applied to control of a SCARA type robot manipulator and simulation results are given

Published in:

Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on  (Volume:4 )

Date of Conference:

20-25 Apr 1997