Analysis of artificial neural networks for pattern-based adaptive control

Daniel Sbarbaro; Tor A Johansen

doi:10.1109/TNN.2006.879762

Analysis of artificial neural networks for pattern-based adaptive control

IEEE Trans Neural Netw. 2006 Sep;17(5):1184-93. doi: 10.1109/TNN.2006.879762.

Authors

Daniel Sbarbaro¹, Tor A Johansen

Affiliation

¹ Department of Electrical Engineering, Universidad de Concepción, Concepción 4089100, Chile. daniel.sbarbaro@udec.cl

PMID: 17001980
DOI: 10.1109/TNN.2006.879762

Abstract

Adaptive pattern-based control strategies adapt their parameters from an analysis of response patterns exhibited by the system. This work presents an analysis of a class of artificial neural network (ANN) pattern-based adaptive control. It provides conditions under which the adaptive algorithm will converge, and it also characterizes the closed-loop stability properties. In addition, a method for monitoring the adaptation is also proposed. Several simulation examples illustrate our findings.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Artificial Intelligence
Cluster Analysis
Computer Simulation
Computing Methodologies
Feedback
Models, Theoretical*
Neural Networks, Computer*
Pattern Recognition, Automated / methods*