リアプノフ直接法による非線形システムのニューラル安定化制御器の設計 [in Japanese] Design of Neural Stabilizing Controller for Nonlinear Systems via Lyapunov's Direct Method [in Japanese]
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This paper is concerned with a neural stabilizing controller of general nonlinear systems. The stabilizing state feedback control law is approximated with a multi-layered 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.
- Transactions of the Society of Instrument and Control Engineers
Transactions of the Society of Instrument and Control Engineers 35(4), 489/495, 1999-04-30
The Society of Instrument and Control Engineers