Transactions of the Korean Society for Noise and Vibration Engineering (한국소음진동공학회논문집)

The Korean Society for Noise and Vibration Engineering (한국소음진동공학회)
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Active Control of Structures Using Lattice Probabilistic Neural Network

격자 확률신경망 기법을 이용한 구조물의 능동 제어

  • 김동현 (군산대학교 해양시스템공학과) ;
  • 장성규 (군산대학교 토목환경공학부) ;
  • 권순덕 (전북대학교 토목공학과) ;
  • 김두기 (군산대학교 토목환경공학부)
  • Published : 2007.07.20
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Abstract

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network(PNN). Therefore. it is the so-called lattice probabilistic neural network(LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However. control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for three story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

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References

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