By Topic

Decentralized Networked Control System Design Using T–S Fuzzy Approach

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)
Changchun Hua ; State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China ; Ding, S.X.

The robust control problem is studied for a class of large-scale networked control systems. The subsystems are in the nonlinear form, and they exchange information through the communication networks. The interconnections considered are nonlinear, and not the traditional linear form, which brings a challenging issue for the decentralized control design. We develop a new memoryless control scheme with the use of the decomposition for each subsystem that is based on the input matrix. By Takagi-Sugeno (T-S) fuzzyfication for each subsystem, the interconnected T-S fuzzy subsystems are obtained. When the upper bound functions of uncertain interconnections are known, we design a decentralized memoryless state feedback controller. When the parameters of bound functions are not available, the adaptive method is used, and the decentralized memoryless adaptive controller is developed. By the construction of a new Lyapunov-Krasovskii functional, we prove the stability of the resultant closed-loop system for the both cases. Finally, we apply the theoretic results to the decentralized controller design of networked interconnected chemical reactor systems. The simulations are performed, and the effectiveness of the proposed method is demonstrated.

Published in:

Fuzzy Systems, IEEE Transactions on  (Volume:20 ,  Issue: 1 )