Abstract
A new paradigm called self-recurrent neural network (SRNN) is proposed. Two SRNNs are utilized in a control system, one as an emulator and the other as a controller. To guarantee convergence and for faster learning, an approach using adaptive learning rate is developed by Lyapunov function. Finally, the neural network control algorithm is developed for on-line control of structural seismic response in real time. Simulation-results have shown that it can effectively control structural seismic response and make it consist with the desired response. © 1998 John Wiley & Sons, Ltd.
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