A T-S Fuzzy Logic Controller for Biped Robot Walking based on Adaptive Network Fuzzy Inference System

被引：0
|
作者：
Cardenas-Maciel, Selene L. [1 ]
Castillo, Oscar [2 ]
Aguilar, Luis T. [3 ]
Castro, Juan R. [4 ]
机构：
[1] Univ Autonoma Baja California, Fac Ciencias Quim & Ingn, Tijuana 22390, BC, Mexico
[2] Inst Tecnol Tijuana, Div Estudios Posgrado & Investigac, Tijuana, Baja California, Mexico
[3] CITEDI IPN, Tijuana 22510, Baja California, Mexico
[4] Div Estudios Posgrado & Investigac, Tijuana, Baja California, Mexico
来源：
2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 | 2010年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页数：8
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