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Improved adaptive control for the discrete‐time parametric‐strict‐feedback form
Author(s) -
González Graciela Adriana
Publication year - 2009
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.1152
Subject(s) - control theory (sociology) , orthogonalization , estimator , parametric statistics , adaptive control , convergence (economics) , mathematics , nonlinear system , subspace topology , correctness , stability (learning theory) , mathematical optimization , computer science , control (management) , algorithm , quantum mechanics , artificial intelligence , mathematical analysis , statistics , physics , machine learning , economics , economic growth
Adaptive control design for a class of single‐input single‐output nonlinear discrete‐time systems in parametric‐strict‐feedback form is re‐visited. No growth restrictions are assumed on the nonlinearities. The control objective is to achieve tracking of a reference signal. As usual, the algorithm derives from the combination of a control law and a parameter estimator (certainty equivalence principle). The parameter estimator strongly lies on the regressor subspace identification by means of an orthogonalization process. Certain drawbacks of previous schemes are analyzed. Several modifications on them are considered to improve the algorithm complexity, control performance and numerical stability. As a result, an alternative control scheme is proposed. When applied to the proposed class of systems, global boundedness and convergence remain as achieved objectives while improving the performance issues of previous schemes. Copyright © 2009 John Wiley & Sons, Ltd.