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Trajectory Linearization Control Based Output Tracking Method for Nonlinear Uncertain System Using Linear Extended State Observer
Author(s) -
Xingling Shao,
Honglun Wang
Publication year - 2016
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.1053
Subject(s) - control theory (sociology) , trajectory , feedback linearization , linearization , nonlinear system , state observer , observer (physics) , affine transformation , state vector , tracking error , controller (irrigation) , taylor series , mathematics , computer science , control (management) , artificial intelligence , mathematical analysis , physics , classical mechanics , astronomy , quantum mechanics , pure mathematics , agronomy , biology
Abstract In this paper, a trajectory linearization control based control law using a linear extended state observer (LESO) is proposed for the output tracking problem of a nonlinear system with uncertainties. First, based on the tracking error dynamics derived by Taylor expansion for the original nonlinear system along the desired trajectory, a feedback linearization (FL) based control law is designed to stabilize a linear time‐varying (LTV) system. To reduce the controller performance sensitive to uncertainties, with partial model information, LESO is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. The closed‐loop stability of the system under the proposed compound scheme is established. Also, simulation results on affine and non‐affine nonlinear uncertain systems are provided to demonstrate the effectiveness of the control strategy. Finally, the issues of sensitivity to sensor noise and the guidelines of tuning parameters are discussed.