Neural integrated fuzzy controller (NiF-T) and real-time implementation of a ball balancing beam (BBB)

Author

Ng, K.C. ; Trivedi, M.M.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA

Volume

2

fYear

1996

fDate

22-28 Apr 1996

Firstpage

1590

Abstract

A controller with blend of neural networks and fuzzy logic is proposed for a nonlinear control problem. Fuzzy logic membership functions are utilized to fuzzify input parameters; neural network interpolates the fuzzy rule set; after defuzzification, the output is used to train a smaller size of neural network; the weights of the later neural network can be adjusted to fine tune the controller. This controller successfully balances balls with one third of the required 27 rules. With learning capability, it approaches its goal more frequently in general

Keywords

fuzzy control; neurocontrollers; nonlinear control systems; position control; ball balancing beam; defuzzification; fuzzy logic membership functions; learning capability; neural integrated fuzzy controller; nonlinear control problem; Computer networks; Control systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Hardware; Humans; Neural networks; Size control;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on

Conference_Location

Minneapolis, MN

ISSN

1050-4729

Print_ISBN

0-7803-2988-0

Type

conf

DOI

10.1109/ROBOT.1996.506939

Filename

506939