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Composite adaptive dynamic surface control using online recorded data
Author(s) -
Pan Yongping,
Sun Tairen,
Yu Haoyong
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3541
Subject(s) - control theory (sociology) , computer science , convergence (economics) , parametric statistics , nonlinear system , adaptive control , stability (learning theory) , online model , system identification , tracking error , lyapunov function , identification (biology) , interval (graph theory) , lyapunov stability , algorithm , mathematics , control (management) , measure (data warehouse) , artificial intelligence , machine learning , data mining , statistics , physics , botany , quantum mechanics , combinatorics , biology , economics , economic growth
Summary This paper presents an online recorded data‐based design of composite adaptive dynamic surface control for a class of uncertain parameter strict‐feedback nonlinear systems, where both tracking errors and prediction errors are applied to update parametric estimates. Differing from the traditional composite adaptation that utilizes identification models and linear filters to generate filtered modeling errors as prediction errors, the proposed composite adaptation integrates closed‐loop tracking error equations in a moving time window to generate modified modeling errors as prediction errors. The time‐interval integral operation takes full advantage of online recorded data to improve parameter convergence such that the application of both identification models and linear filters is not necessary. Semiglobal practical asymptotic stability of the closed‐loop system is rigorously established by the time‐scales separation and Lyapunov synthesis. The major contribution of this study is that composite adaptation based on online recorded data is achieved at the presence of mismatched uncertainties. Simulation results have been provided to verify the effectiveness and superiority of this approach. Copyright © 2016 John Wiley & Sons, Ltd.