TITLE

Adaptive Fuzzy Model Predictive Control for Non-minimum Phase and Uncertain Dynamical Nonlinear Systems

AUTHOR(S)
Tran Quang Tuan; Phan Xuan Minh
PUB. DATE
April 2012
SOURCE
Journal of Computers;Apr2012, Vol. 7 Issue 4, p1014
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
this paper introduces a method to design a robust adaptive predictive control based on Fuzzy model. The plant to be used as predictive model is simulated by Takagi-Sugeno Fuzzy Model, and the optimization problem is solved by a Genetic Algorithms or Branch and Bound. The method to tune parameters of the model predictive controller based on Lyapunov stability theorem is presented in this paper to bring higher control performance and guaranty Global Asymptotical Stable (GAS) for the closedloop system. This method is used for nonlinear systems with non-minimum phase (CSTR), uncertain dynamical systems and nonlinear DC motor. The simulation results for the Continuous Stirrer Tank Reactor (CSTR), nonlinear uncertain dynamical system and nolinear DC motor are used for verifying the proposal method.
ACCESSION #
76108469

 

Related Articles

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics