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Recursive Gauss–Seidel algorithm for direct self‐tuning control
Author(s) -
Hatun Metin,
Koçal Osman Hilmi
Publication year - 2012
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.1296
Subject(s) - gauss–seidel method , controller (irrigation) , control theory (sociology) , stability (learning theory) , recursive least squares filter , algorithm , computer science , mathematics , iterative method , control (management) , adaptive filter , artificial intelligence , machine learning , agronomy , biology
SUMMARY A recursive algorithm based on the use of Gauss–Seidel iterations is introduced to adjust the parameters of a self‐tuning controller for minimum phase and a class of nonminimum phase discrete‐time systems. The proposed algorithm is called the Recursive Gauss–Seidel (RGS) algorithm and is used to update the controller parameters directly. The use of the RGS algorithm with a generalized minimum variance control law is also given for nonminimum phase systems, and a forgetting factor is used to track the time‐varying parameters. Furthermore, the overall stability of the closed‐loop system is proven by using the Lyapunov stability theory. Using computer simulations, the performance of the RGS algorithm is examined and compared with the widely used recursive least squares algorithm.Copyright © 2011 John Wiley & Sons, Ltd.