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Design of neural stabilizing controller for nonlinear systems via Lyapunov's direct method

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2 Author(s)
Shimizu, K. ; Fac. of Sci. & Technol., Keio Univ., Yokohama, Japan ; Ito, K.

This paper deals with a neural stabilizing controller of general nonlinear systems. The stabilizing state feedback control law is approximated with a multilayer neural network. Connection weights in the neural controller are determined by a min-max algorithm such that the Lyapunov stability theorem holds via a control Lyapunov function

Published in:

Neural Networks, 1999. IJCNN '99. International Joint Conference on  (Volume:3 )

Date of Conference:

1999