Translated Title
Predictive control of structural vibration based on state observer
Translated Abstract
Aiming at the time lag of structural vibration control and the demand of feedback control in full structural state, a sequential optimal predictive modal control （SOPMC） algorithm based on state observer was proposed. According to the structural response of feedback, the full state of structure was observed with the state observer, and the real-time control force was calculated with the SOPMC algorithm. The radial basis function neural network （RBFNN） was designed through taking the structural response of feedback and the calculated control force as input and with considering the time lag of control system, and then a sequential optimal predictive modal controller based on full-state observer was developed. A seismic response control was carded out for an actual vibration isolated 330 kV voltage instrument transformer with distribution parameters. The simulation results show that without the presence of time lag, the control effect of SOPMC algorithm is equivalent to that of sequential optimal modal control （SOMC） algorithm. With the presence of time lag, the SOPMC algorithm can effectively overcome the influence of time lag on the optimal predictive control algorithm, and exhibits good control effect.
Translated Keyword
time lag
seismic response
state reconstruction
predictive control
neural network
control algorithm
structural vibration control
state observer
Access Number
WF:perioarticalsygydxxb201104017
Corresponding authors email
