期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 47, 期 10, 页码 3075-3087出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2016.2607166
关键词
Adaptive neural networks control; backstepping; nonlower triangular nonlinear systems
类别
资金
- National Natural Science Foundation of China [61304002, 61333012, 61573112, U1509217, 61622302, 61673072]
- Australian Research Council [DP140102180, LP140100471, LE150100079]
This paper considers the problem of adaptive neural control of nonlower triangular nonlinear systems with unmodeled dynamics and dynamic disturbances. The design difficulties appeared in the unmodeled dynamics and nonlower triangular form are handled with a dynamic signal and a variable partition technique for the nonlinear functions of all state variables, respectively. It is shown that the proposed controller is able to ensure the semi-global boundedness of all signals of the resulting closed-loop system. Furthermore, the system output is ensured to converge to a small domain of the given trajectories. The main advantage about this research is that a neural networks-based tracking control method is developed for uncertain nonlinear systems with unmodeled dynamics and nonlower triangular form. Simulation results demonstrate the feasibility of the newly presented design techniques.
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