Title :
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
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;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596653
