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Control of structural seismic response by self‐recurrent neural network (SRNN)
Author(s) -
He YuAo,
Wu Jianjun
Publication year - 1998
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/(sici)1096-9845(199807)27:7<641::aid-eqe741>3.0.co;2-d
Subject(s) - artificial neural network , convergence (economics) , control theory (sociology) , controller (irrigation) , computer science , lyapunov function , adaptive control , control (management) , function (biology) , engineering , control engineering , artificial intelligence , physics , nonlinear system , quantum mechanics , evolutionary biology , agronomy , economics , biology , economic growth
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.