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Adaptive control of linearly parameterized nonaffine nonlinear systems via dynamic matching
Author(s) -
Wu Chengshuai,
Chen Jian
Publication year - 2020
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.5164
Subject(s) - control theory (sociology) , nonlinear system , duffing equation , parameterized complexity , parametric statistics , adaptive control , affine transformation , computer science , lyapunov function , matching (statistics) , mathematics , control (management) , algorithm , physics , artificial intelligence , statistics , quantum mechanics , pure mathematics
Summary This article studies an adaptive control problem for nonaffine nonlinear systems with linear parametric uncertainty. Inspired by the affine system case, the studied nonaffine nonlinear systems are specified such that the ideal control input is implicitly defined by a matching equation stemming from a Lyapunov‐based analysis. The core idea of control design is to solve the matching equation in a dynamic manner. Toward this end, a dynamic state‐feedback law, together with an adaptation law for the unknown parameters, is developed such that global asymptotic stabilization is theoretically guaranteed. The proposed method is validated on a Duffing‐Holmes oscillator with a nonaffine input and a multi‐input numerical example.