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Extended filtering high‐gain output feedback controller for a class of uncertain nonlinear systems subject to external disturbances
Author(s) -
Ma Tong
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.4993
Subject(s) - control theory (sociology) , robustness (evolution) , nonlinear system , computer science , filter (signal processing) , lipschitz continuity , inversion (geology) , control engineering , engineering , control (management) , mathematics , artificial intelligence , physics , quantum mechanics , biology , gene , mathematical analysis , paleontology , biochemistry , chemistry , structural basin , computer vision
Abstract In this article, an extended filtering high‐gain output feedback controller is developed for a class of uncertain nonlinear systems subject to external disturbances. The nonlinearities under consideration satisfy a semiglobal Lipschitz condition. The proposed control architecture integrates the extended state observer (ESO), high gain, and low‐pass filter together. None of them is used alone. The ESO can not only estimate the unknown internal state, but also deliver a good property of disturbance rejection simultaneously due to the presence of high gain. Since the high gain deteriorates the robustness of the system, a low‐pass filtering mechanism is added in the control law to filter away aggressive signals and recover the robustness. The filtering control law is designed to compensate the nonlinear uncertainties and deliver a good tracking performance with guaranteed stability. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. Since the virtual reference system defines the best performance that can be achieved by the closed‐loop system, the uniform performance bounds are derived for the states and control signals via comparison. Numerical examples are provided to illustrate the effectiveness of the novel design via comparisons with the model reference adaptive control method and L 1 adaptive controller.