By Topic

Decentralized control of large scale interconnected systems using adaptive neural network-based dynamic surface control

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

3 Author(s)
Mehraeen, S. ; Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA ; Jagannathan, S. ; Crow, M.L.

A novel decentralized controller using the dynamic surface control (DSC) is proposed for a class of uncertain large scale interconnected nonlinear systems in strict-feedback form while relaxing the ldquoexplosion of complexityrdquo problem which is observed in the typical backstepping approach. The matching condition is not assumed when dealing with the interconnection terms. Neural networks (NNs) are utilized to approximate the uncertainties in both subsystem and interconnected terms. By using novel NN weight update laws, it is demonstrated using Lyapunov stability that the closed-loop signals are asymptotically stable in the presence of NN approximation errors in contrast with the uniform ultimate boundedness result that is common in the literature with NN-based DSC and backstepping schemes. Simulation results of the controller performance for a nonlinear decentralized system justify theoretical conclusions.

Published in:

Neural Networks, 2009. IJCNN 2009. International Joint Conference on

Date of Conference:

14-19 June 2009