Title :
Adaptive fuzzy logic controller for FES-computer simulation study
Author :
Wang, Feng ; Andrews, Brian J.
Author_Institution :
Dept. of Appl. Sci. in Med., Alberta Univ., Edmonton, Alta., Canada
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 :
adaptive control; biocontrol; bioelectric phenomena; controllers; digital simulation; fuzzy logic; learning (artificial intelligence); medical expert systems; muscle; neurophysiology; optimal control; orthotics; adaptive fuzzy logic controller; computer model; computer simulation study; functional electrical stimulation control; fuzzy IF-THEN rules; on-line learning ability; online reinforcement learning algorithm; optimal control rules; prior expert knowledge; rules fine-tuning; swing leg; trainable network structure; Adaptive control; Automatic control; Control systems; Fuzzy logic; Hip; Learning; Leg; Medical simulation; Neuromuscular stimulation; Optimal control; Programmable control; Torque control;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.411981
