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Stable direct adaptive periodic control using only plant order knowledge
Author(s) -
Bayard David S.
Publication year - 1996
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199611)10:6<551::aid-acs398>3.0.co;2-i
Subject(s) - control theory (sociology) , adaptive control , a priori and a posteriori , convergence (economics) , stability (learning theory) , transient (computer programming) , minimum phase , set (abstract data type) , computer science , control (management) , mathematics , phase (matter) , artificial intelligence , physics , machine learning , philosophy , epistemology , quantum mechanics , economics , programming language , economic growth , operating system
The main contribution of this paper is to put stability requirements for convergence of direct adaptive periodic controllers on an equal footing with requirements for indirect adaptive periodic control as set forth by Lozano. The resulting stability condition is simply that the plant order is known a priori . No other prior plant knowledge is used (e.g. relative degree, high‐frequency gain, etc.) and persistent excitation is not required. More importantly, no assumption or knowledge is required as to whether the plant is minimum or non‐minimum phase. A numerical example is given to demonstrate the method and some guidelines are given for improving the adaptive transient response.