Neural network adaptive control of systems with input saturation

E. N. Johnson, A. J. Calise

Research output: Contribution to journalConference articlepeer-review

99 Scopus citations

Abstract

In the application of adaptive flight control, significant issues arise due to limitations on the plant inputs, such as actuator displacement limits. The concept of utilizing a modified reference model to prevent an adaptation law from "seeing" this system-input characteristic is described. The method allows correct adaptation while the plant input is saturated. To apply the method, estimates of actuator positions must be found. However, the adaptation law can correct for errors in these estimates. A theorem of boundedness for all system signals is included for a single hidden layer neural network adaptive law. The domain of attraction is also discussed.

Original languageEnglish (US)
Pages (from-to)3527-3532
Number of pages6
JournalProceedings of the American Control Conference
Volume5
DOIs
StatePublished - 2001
Event2001 American Control Conference - Arlington, VA, United States
Duration: Jun 25 2001Jun 27 2001

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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