【摘要】 针对结构振动控制时滞问题及反馈控制对结构全状态的需求,提出了一种基于状态观测器的序列最优预测模态控制算法.根据反馈的结构响应,通过状态观测器观测估计结构的全状态,通过序列最优预测模态控制算法计算实时控制力,将反馈的结构响应和计算的控制力作为输入,考虑控制系统的时滞,设计径向基神经网络(RBFNN),形成基于状态观测器的序列最优预测模态控制器.对一带分布参数实际隔震的330 kV电压互感器进行地震响应控制,仿真结果表明,基于状态观测器的序列最优预测模态控制算法,在无时滞的情况下与基于状态观测器的序列最优模态控制算法控制效果相当,在有时滞的情况下能有效克服时滞对最优预测控制算法的影响,控制效果良好.更多还原

【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 carried 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.更多还原