Please use this identifier to cite or link to this item: https://doi.org/10.1109/3477.809035
Title: Adaptive neural network control of nonlinear systems by state and output feedback
Authors: Ge, S.S. 
Hang, C.C. 
Zhang, T.
Keywords: Adaptive control
High-gain observer
Neural networks
Nonlinear system
Output feedback control
Issue Date: 1999
Source: Ge, S.S.,Hang, C.C.,Zhang, T. (1999). Adaptive neural network control of nonlinear systems by state and output feedback. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 29 (6) : 818-828. ScholarBank@NUS Repository. https://doi.org/10.1109/3477.809035
Abstract: This paper presents a novel control method for a general class of nonlinear systems using neural networks (NN's). Firstly, under the conditions of the system output and its time derivatives being available for feedback, an adaptive state feedback NN controller is developed. When only the output is measurable, by using a high-gain observer to estimate the derivatives of the system output, an adaptive output feedback NN controller is proposed. The closed-loop system is proven to be semi-globally uniformly ultimately bounded (SGUUB). In addition, if the approximation accuracy of the neural networks is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussions. © 1999 IEEE.
Source Title: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/61761
ISSN: 10834419
DOI: 10.1109/3477.809035
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