Identifier based interval type-2 fuzzy tracking control

Author

Tsung-Chih Lin ; Chung-Ching Wang ; I-Shin Liu ; Balas, Valentina E.

Author_Institution

Dept. of Electron. Eng., Feng-Chia Univ., Taichung, Taiwan

fYear

2013

fDate

7-10 July 2013

Firstpage

1

Lastpage

8

Abstract

Based on system identifier, interval type-2 fuzzy neural network (IT2FNN) tracking control for a class of unknown nonlinear dynamic system is developed in this paper. In order to fully handle or accommodate the linguistic and numerical uncertainties associated with dynamic unstructured environments, an IT2FNN controller equipped with a learning algorithm is developed. In the meantime, an IT2FNN identifier is incorporated into the IT2FNN controller to predict the system sensitivity of the unknown nonlinear dynamic system. The comparison between type-1 FNN (T1FNN) controller and IT2FNN controller is given to sufficiently illustrate the effectiveness of the proposed control scheme.

Keywords

fuzzy control; identification; learning (artificial intelligence); neurocontrollers; nonlinear control systems; numerical analysis; sensitivity analysis; uncertain systems; IT2FNN identifier; IT2FNN tracking control; T1FNN controller; dynamic environments; learning algorithm; linguistic uncertainties; numerical uncertainties; system identifier-based interval type-2 fuzzy tracking control; system sensitivity prediction; type-1 FNN controller; unknown nonlinear dynamic system; Educational institutions; Fuzzy control; Fuzzy neural networks; Nonlinear dynamical systems; Pragmatics; Trajectory; Uncertainty; Interval type-2 fuzzy neural network; identification; nonlinear systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ), 2013 IEEE International Conference on

Conference_Location

Hyderabad

ISSN

1098-7584

Print_ISBN

978-1-4799-0020-6

Type

conf

DOI

10.1109/FUZZ-IEEE.2013.6622428

Filename

6622428