Neural network learning algorithm for a class of interconnected nonlinear systems

Authors:
S. N. Huang;K. K. Tan;T. H. Lee
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, Mechatronics and Automation Laboratory, 4 Engineering Drive 3, 10 Kent Ridge Crescent, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Mechatronics and Automation Laboratory, 4 Engineering Drive 3, 10 Kent Ridge Crescent, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Mechatronics and Automation Laboratory, 4 Engineering Drive 3, 10 Kent Ridge Crescent, Singapore
Venue:
Neurocomputing
Year:
2009

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Abstract

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.