Real-time neurofuzzy control for an underactuated robot

Author

Lara-Rojo, Fernando ; Sanchez, Edgar N. ; Cuevas, Erik V.

Author_Institution

ITESO Univ., Mexico

Volume

4

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

2220

Abstract

We use a neurofuzzy approach, the NEFCON model, to generate and optimize a fuzzy controller for real-time control of an underactuated robot: the Pendubot, which consists of a two link inverted pendulum actuated only at the first join. The NEFCON learning algorithm is able to learn fuzzy rules as well as fuzzy sets. We present the results of the learning process for a fuzzy controller to balance the Pendubot in its highest inverted position, simulation results, and real-time results. The extension of this work to include the learning process of a swing-up procedure is in progress

Keywords

control system synthesis; fuzzy control; fuzzy neural nets; learning (artificial intelligence); neurocontrollers; optimal control; pendulums; real-time systems; robots; NEFCON model; Pendubot; fuzzy controller; fuzzy rules; fuzzy sets; optimal fuzzy controller; real-time neurofuzzy control; swing-up procedure learning; two-link inverted pendulum; underactuated robot; Control systems; Electronic mail; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Machine intelligence; Multilayer perceptrons; Neural networks; Robots;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.833406

Filename

833406