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Disturbance compensation based model‐free adaptive tracking control for nonlinear systems with unknown disturbance
Author(s) -
Li Haifeng,
Wang Yingchun,
Pang Mengmeng
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2230
Subject(s) - control theory (sociology) , disturbance (geology) , nonlinear system , compensation (psychology) , linearization , feedback linearization , tracking (education) , computer science , adaptive control , control engineering , engineering , control (management) , artificial intelligence , psychology , paleontology , pedagogy , physics , quantum mechanics , psychoanalysis , biology
Abstract This paper considers a novel model‐free adaptive tracking control for nonlinear perturbed systems. A general dynamic linearization model with disturbance input is first developed for nonlinear systems based on the pseudo‐partial derivatives (PPDs) method and input/output (I/O) data. Due to the unknown disturbance input, an online disturbance estimation algorithm is proposed based on optimization by minimizing a cost function. Furthermore, an adaptive tracking control strategy with disturbance compensation is developed, such that the tracking error of nonlinear systems is convergent and closed‐loop systems are strongly robust. Finally, a comparing simulation is provided to demonstrate the effectiveness of the proposed approach.