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Active Control for Seismic Response Reduction Using Probabilistic Neural Network  

Kim, Doo-Kie (군산대학교 토목환경공학부)
Lee, Jong-Jae (한국과학기술원 스마트사회기반시설연구센터)
Chang, Seong-Kyu (군산대학교 토목환경공학부)
Choi, In-Jung (군산대학교 토목환경공학부)
Publication Information
Journal of the Korea institute for structural maintenance and inspection / v.11, no.1, 2007 , pp. 103-112 More about this Journal
Abstract
Recently structures become longer and higher because of the developments of new materials and construction techniques. However, such modern structures are susceptible to excessive structural vibrations, which may induce problems of serviceability and structural damages. In this paper we attempt to control structural vibration using the probabilistic neural network(PNN) and the artificial neural network(ANN) based on the training pattern that consist of only the structural state vector and the control force. The state vectors of the structure and control forces made by linear quadratic regulator(LQR) algorithm are used for training pattern of PNN and ANN. The proposed algorithm is applied for the vibration control of the three story shear building under Northridge earthquake. Control results by the proposed PNN and ANN are compared with each other.
Keywords
Probabilistic nerual network(PNN); Training pattern; Active control; Control gain;
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