NDLI: Design and Analysis of a Novel L1 Adaptive Controller, Part I: Control Signal and Asymptotic Stability

Content Provider	IEEE Xplore Digital Library
Author	Chengyu Cao Hovakimyan, N.
Copyright Year	2006
Description	Author affiliation: Aerosp. & Ocean Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA (Chengyu Cao; Hovakimyan, N.)
Abstract	In this paper, we develop a novel adaptive control architecture that ensures that the input and output of an uncertain linear system track the input and output of a desired linear system during the transient phase, in addition to the asymptotic tracking. These features are established by first performing an equivalent reparametrization of MRAC, the main difference of which from MRAC is in definition of the error signal for adaptive laws. This new architecture, called companion model adaptive controller (CMAC), allows for incorporation of a low-pass filter into the feedback-loop that enables to enforce the desired transient performance by increasing the adaptation gain. For the proof of asymptotic stability, the $Lscr_{1}$ gain of a cascaded system, comprised of this filter and the closed-loop desired reference model, is required to be less than the inverse of the upper bound of the norm of unknown parameters used in projection based adaptation laws. Moreover, the new $Lscr_{1}$ adaptive controller is guaranteed to stay in the low-frequency range. Simulation results illustrate the theoretical findings
Sponsorship	American Automatic Control Council IFAC
Starting Page	3397
Ending Page	3402
File Size	565392
Page Count	6
File Format	PDF
ISBN	1424402093
e-ISBN	1424402107
DOI	10.1109/ACC.2006.1657243
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Signal design Signal analysis Programmable control Adaptive control Asymptotic stability Linear systems Low pass filters Adaptive filters Performance gain Upper bound
Content Type	Text
Resource Type	Article

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