A T-S Fuzzy Logic Controller for biped robot walking based on adaptive network fuzzy inference system

Author

Cardenas-Maciel, Selene L. ; Castillo, Oscar ; Aguilar, Luis T. ; Castro, Juan R.

Author_Institution

Fac. de Cienc. Quimicas e Ing., Univ. Autonoma de Baja California, Tijuana, Mexico

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

8

Abstract

A neuro-fuzzy learning algorithm is applied to design a Takagi-Sugeno type Fuzzy Logic Controller (T-S FLC) for a biped robot walking problem. The control design considers an output function imposed on the feedback and several TS-FLC models are determined each by ANFIS, which represent a piece-wise control inputs that together to perform a walking cycle. Two simulations of the closed-loop system for generation of walking motions are given, where we assume that the joint positions and the whole state of the system are available for controller feedback respectively.

Keywords

adaptive control; closed loop systems; control engineering computing; control system synthesis; feedback; fuzzy control; fuzzy neural nets; fuzzy reasoning; learning (artificial intelligence); legged locomotion; motion control; neurocontrollers; ANFIS; T-S fuzzy logic controller; TS-FLC model; Takagi-Sugeno type fuzzy logic controller; adaptive network fuzzy inference system; biped robot walking; closed-loop system; control design; controller feedback; neuro-fuzzy learning algorithm; output function; piece-wise control; walking cycle; walking motion; Adaptation model; Leg; Legged locomotion; Mathematical model; Robot kinematics; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2010 International Joint Conference on

Conference_Location

Barcelona

ISSN

1098-7576

Print_ISBN

978-1-4244-6916-1

Type

conf

DOI

10.1109/IJCNN.2010.5596653

Filename

5596653