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Model reference adaptive control using a low‐order controller
Author(s) -
Miller Daniel E.
Publication year - 2001
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/acs.666
Subject(s) - control theory (sociology) , minimum phase , controller (irrigation) , constant (computer programming) , dimension (graph theory) , reference model , sign (mathematics) , adaptive control , upper and lower bounds , tracking error , mathematics , value (mathematics) , computer science , stability theory , control (management) , phase (matter) , nonlinear system , statistics , physics , quantum mechanics , mathematical analysis , chemistry , organic chemistry , software engineering , artificial intelligence , pure mathematics , agronomy , biology , programming language
In the model reference adaptive control problem, the goal is to force the error between the plant output and the reference model output asymptotically to zero. The classical assumptions on a single‐input–single‐output (SISO) plant is that it is minimum phase, and that the plant relative degree, the sign of the high‐frequency gain, and an upper bound on the plant order are known. Here we consider a modified problem in which the objective is weakened slightly to that of requiring that the asymptotic value of the error be less than a (arbitrarily small) pre‐specified constant. Using recent results on the design of generalized holds for model reference tracking, here we present a new switching adaptive controller of dimension two which achieves this new objective for every minimum phase SISO system; no structural information is required. Copyright © 2001 John Wiley & Sons, Ltd.