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Neural network learning algorithm for a class of interconnected nonlinear systems
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DOI：10.1016/j.neucom.2008.03.013.png)
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Abstract
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In this paper, an adaptive neural network algorithm is developed for a class of interconnected nonlinear systems. Neural networks (NNs) are used to approximate the unknown nonlinear functions and interconnections in the subsystems. A systematic approach is established to synthesize the adaptive NN learning control scheme that ensures the boundedness of all the signals in the closed-loop system. The effectiveness of the proposed scheme is demonstrated by computer simulations. (C) 2008 Elsevier B.V. All rights reserved.
Keywords:
Adaptive control
Neural network learning
Nonlinear systems
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