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Semiactive Neurocontrol for Seismic Response Reduction Using Smart Damping Strategy
Authors:Hyung-Jo Jung  Heon-Jae Lee  Woo-Hyun Yoon  Ju-Won Oh  In-Won Lee
Affiliation:1Assistant Professor, Dept. of Civil and Environmental Engineering, Sejong Univ., Seoul 143-747, Korea.
2Graduate Student, Dept. of Civil and Environmental Engineering, KAIST, Daejeon 305-701, Korea.
3Professor, Graduate School of Industry and Environment, Kyungwon Univ., 65 Bokjeong-dong, Sujeong-gu, Seongnam 461-701, Korea.
4Professor, Dept. of Civil and Environmental Engineering, Hannam Univ., Daejeon, 306-791, Korea.
5Professor, Dept. of Civil and Environmental Engineering, KAIST, Daejeon 305-701, Korea.
Abstract:A new semiactive control strategy that combines a neurocontrol system with a smart damper is proposed to reduce seismic responses of structures. In the proposed semiactive control system, the improved neurocontroller, which was developed by employing a training algorithm based on a cost function and a sensitivity evaluation algorithm to replace an emulator neural network, produces the desired active control force, and then a bang-bang-type controller clips the control forces that cannot be achieved by a smart damper (e.g., a variable orifice damper, controllable fluid damper, etc.). Therefore, the proposed semiactive control strategy is fail-safe in that the bounded-input, bounded-output stability of the controlled structure is guaranteed. Numerical simulation results show that the proposed semiactive control system that employs a neural network-based control algorithm is quite effective in reducing seismic responses.
Keywords:Active control  Control systems  Seismic response  Damping  Algorithms  
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