Practical stability issues in CMAC neural network control systems

Fu-Chuang Chen*, Chih Horng Chang

*Corresponding author for this work

Research output: Contribution to journalArticle

65 Scopus citations

Abstract

The cerebellar model articulation controller (CMAC) neural network is a practical tool for improving existing nonlinear control systems. A typical simulation study is used to clearly demonstrate that the CMAC can effectively reduce tracking error, but can also destabilize a control system which is otherwise stable. Then quantitative studies are presented to search for the cause of instability in the CMAC control system. Based on these studies, methods are discussed to improve system stability. Experimental results on controlling a real world system are provided to support the findings in simulations.

Original languageEnglish
Pages (from-to)86-91
Number of pages6
JournalIEEE Transactions on Control Systems Technology
Volume4
Issue number1
DOIs
StatePublished - 1 Dec 1996

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