Identification and Control of Dynamic Systems via Adaptive Neural Networks
Morles, E.C. and Mort, N.
(1991)
Identification and Control of Dynamic Systems via Adaptive Neural Networks.
Research Report.
Acse Report 433
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
In this work we study some applications of multilayer perceptron neural networks to identify and to control certain types of dynamic systems. Two different methods to update the weights of the neural networks are explored: a variable structure control formulation and a gradient descent approach. Both methods are digitally simulated and their performances in parameter identification are compared.
Also, we present an adaptive model reference control scheme and an indirect self-tuning control scheme based on a multilayer perceptron neural network. Examples of the simulated responses for both schemes are obtained using different linear plants.
Metadata
Item Type:
Monograph
Authors/Creators:
Morles, E.C.
Mort, N.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)