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Observer‐based adaptive DSC with nonlinear gain and recursive sliding mode for non‐affine nonlinear systems
Author(s) -
Yang Yang,
Meng Qing,
Yue Dong,
Ge Hui,
Hou Xiaolei
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.2278
Subject(s) - control theory (sociology) , nonlinear system , observer (physics) , sliding mode control , affine transformation , lyapunov function , computer science , artificial neural network , variable structure control , mathematics , control (management) , artificial intelligence , physics , quantum mechanics , pure mathematics
The output feedback control issue is addressed for a class of non‐affine nonlinear systems in this paper. In the situation that the internal states of the system are not available, we design a neural network (NN) observer and employ NNs to compensate unknown dynamics in real time. Considering the error and dynamic performance of each subsystem, we introduce the recursive sliding‐mode dynamic surface method and nonlinear gain function into the output feedback control strategy. The proposed strategy not only enhances the range of control parameters but also makes a compromise between the control accuracy and dynamic performance. The boundedness of the closed‐loop signals is proven by the Lyapunov theory. Finally, the simulation results verify the validity of the control strategy.