Practical stability issues in CMAC neural network control systems

Fu-Chuang Chen*, Chih Horng Chang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


The CMAC neural network is a practical tool for improving existing nonlinear control systems. Although many researchers report that it have good performance, our results suggest that the CMAC control system can go unstable. The unstable phenomena are quantitatively studied, and some methods for improving stability are suggested.

Original languageEnglish
Article number735109
Pages (from-to)2945-2946
Number of pages2
JournalProceedings of the American Control Conference
StatePublished - 29 Jun 1994
EventProceedings of the 1994 American Control Conference. Part 1 (of 3) - Baltimore, MD, USA
Duration: 29 Jun 19941 Jul 1994


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