Adaptive fuzzy logic controller for FES-computer simulation study

17 December 2002

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 1, 406-407
https://doi.org/10.1109/iembs.1994.411981

Abstract

An adaptive fuzzy logic controller (FLC), based on a trainable network structure, is designed for functional electrical stimulation (FES) control. A prior expert knowledge can be incorporated as fuzzy IF-THEN rules. An online reinforcement learning algorithm is employed for learning optimal control rules or fine-tuning the existing control rules. This adaptive FLC is applied to a computer model of swing leg and demonstrates its on-line learning ability.

Keywords

PROGRAMMABLE CONTROL
ADAPTIVE CONTROL
FUZZY LOGIC
OPTIMAL CONTROL
NEUROMUSCULAR STIMULATION
LEARNING
LEG

This publication has 1 reference indexed in Scilit:

Learning and tuning fuzzy logic controllers through reinforcements
IEEE Transactions on Neural Networks, 1992