A novel identification method for generalized T-S fuzzy systems
Original version
Huang, L., Wang, K., Shi, P., & Karimi, H.R. (2012). A novel identification method for generalized T-S fuzzy systems. Mathematical Problems in Engineering, 2012. doi: 10.1155/2012/893807 10.1155/2012/893807Abstract
In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
Description
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807