By Topic

A new PID-type Fuzzy neural network controller based on Genetic Algorithm with improved Smith predictor

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)
Ruiqi Wang ; Sch. of Control Sci. & Eng., Univ. of Shandong, Jinan, China ; Ke Li ; Naxin Cui ; Chenghui Zhang

Owing to the problem of control difficulty for the complex system, which has the characteristics of the large inertia, the pure time-delay and the model uncertainty in the industrial processes, a new PID-type fuzzy neural network controller (FNNC) based on Takagi-Sugeno-Kang (TSK) inference is proposed. Real-coded Chaotic Quantum-inspired Genetic Algorithm (RCQGA) is used to optimize the membership function parameters and TSK parameter sets simultaneously with faster convergence speed and more powerful optimizing ability. The pure time-delay effect of the complex object is compensated by a Smith predictor combined with Radial Basis Function (RBF) neural network identifier. The structure and control tactics of the controller are presented and tested by simulations and experiments in the heating furnace system. The proposed algorithm, as confirmed by the results of simulation and experiment compared with the Smith-Fuzzy-PID controller, exhibits good dynamic adjustment, high steady-state accuracy, strong resistant ability to interference and good robustness.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009