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Adaptive control of non‐minimum phase systems
Author(s) -
Campi Marco C.
Publication year - 1995
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.4480090203
Subject(s) - minimum phase , control theory (sociology) , adaptive control , stability (learning theory) , mathematics , consistency (knowledge bases) , exponential stability , extension (predicate logic) , phase (matter) , work (physics) , stability theory , control system , property (philosophy) , strong consistency , control (management) , mathematical optimization , computer science , statistics , engineering , nonlinear system , estimator , artificial intelligence , chemistry , quantum mechanics , machine learning , programming language , mechanical engineering , physics , organic chemistry , electrical engineering , philosophy , geometry , epistemology
Adaptive control schemes based on the recursive least squares (RLS) estimation technique are analysed in this paper. First, under the assumption that the asymptotically estimated system does not present pole‐zero cancellations, a general stability result is proven. Such a result does not require the system to be minimum phase. Then it is shown that on the grounds of the stability property the control system attains asymptotic optimality. The results of the present paper rely on previous work by Rootzen and Sternby concerning the consistency of RLS estimates and are intended as a first step in the extension of Kumar's work in adaptive control to non‐minimum phase systems.