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A new approach to model reference adaptive control
Author(s) -
Duarte Manuel A.,
Narendra Kumpati S.
Publication year - 1989
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.4480030106
Subject(s) - control theory (sociology) , controller (irrigation) , lyapunov function , adaptive control , computer science , stability (learning theory) , ideal (ethics) , reference model , transient (computer programming) , control (management) , mathematics , control engineering , engineering , artificial intelligence , nonlinear system , machine learning , philosophy , physics , software engineering , epistemology , quantum mechanics , agronomy , biology , operating system
A new approach to model reference adaptive control, based on a combination of direct and indirect control methods, is introduced in this paper. The controller structure is identical to that used in the direct method, but the algorithm used to update the controller parameters depends both on the output error as in direct control and on the plant parameter estimates as in indirect control. The global stability of the overall system is assured by the existence of a Lyapunov function. In the ideal case discussed here, the combined approach results in improved transient response with smaller amplitude of the control input as compared to the constituent methods.