DocumentCode
3335530
Title
A neuromorphic controller with a human teacher
Author
Guez, Allon ; Selinsky, John
Author_Institution
Dept. of Electron. Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear
1988
fDate
24-27 July 1988
Firstpage
595
Abstract
Trainable adaptive controllers (TACs) are a subset of process controllers in which much of the design is done online by means of training rather than programming. The authors show how a neural-network-based architecture may be used to implement a general-purpose TAC. An example of controlling a cart-pole system (an inverted pendulum mounted on a cart) is provided. It is found that filtering of the human-teacher training data, using a dynamic model of the teacher, significantly improves the neuromorphic TAC´s performance.<>
Keywords
adaptive control; computer architecture; computerised control; learning systems; neural nets; pendulums; cart-pole system; inverted pendulum; neural-network-based architecture; neuromorphic controller; online training; process controllers; trainable adaptive controllers; Adaptive control; Computer architecture; Digital control; Learning systems; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1988., IEEE International Conference on
Conference_Location
San Diego, CA, USA
Type
conf
DOI
10.1109/ICNN.1988.23976
Filename
23976
Link To Document