Command governor-Based adaptive control

Tansel Yucelen, Eric Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations


Even though an important prerequisite for an adaptive controller is the ability to adapt fast in the face of large system uncertainties, fast adaptation with high-gain learning rates can be a serious limitation due to the fact that it can possibly yield to high-frequency oscillations especially during the transient system response. Therefore, achieving fast adaptation with low-gain learning rates and predictable transient and steady-state system response is the challenge for the adaptive control theorist today. To that end, we introduce a novel command governor architecture for adaptive stabilization and command following. Specifically, the proposed command governor is a linear dynamical system which adjusts the trajectories of a given command in order to follow an ideal reference system both in transient time and steady-state without resorting to high-gain learning rates in the adaptation law. It is shown that by choosing the design parameter of the command governor, the controlled nonlinear uncertain dynamical system can approach a Hurwitz linear time-invariant dynamical system with L∞ input-output signals. This provides a systematic framework for verification and validation of adaptive control systems and the proposed command governor can be used in a complimentary way with many other approaches to adaptive control.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference 2012
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Print)9781600869389
StatePublished - 2012
EventAIAA Guidance, Navigation, and Control Conference 2012 - Minneapolis, MN, United States
Duration: Aug 13 2012Aug 16 2012

Publication series

NameAIAA Guidance, Navigation, and Control Conference 2012


OtherAIAA Guidance, Navigation, and Control Conference 2012
Country/TerritoryUnited States
CityMinneapolis, MN

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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