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基于人工神经网络方法,在考虑上部结构的刚度和阻尼的条件下,通过计算基底摩擦力的大小,对滑移隔震结构的半主动控制方法进行了研究。实例计算表明,通过半主动控制的滑移隔震结构不但具有较好的隔震效果,且能有效地减小基底的最大滑移量及残余位移。通过与Bang-Bang控制和瞬时最优控制算法的对比分析表明:基于人工神经网络控制算法的控制效果优于其它控制算法,具有反馈量少、稳健性强等特点。
Based on the artificial neural network method, considering the stiffness and damping of the superstructure, the semi-active control method of the slippage isolation structure is studied by calculating the friction force of the basement. The example calculation shows that the sliding isolation structure controlled by semi-active control not only has better isolation effect, but also can effectively reduce the maximum slippage and residual displacement of the substrate. The comparison between Bang-Bang control and instantaneous optimal control algorithm shows that the control effect based on artificial neural network control algorithm is better than other control algorithms, and has the characteristics of less feedback and strong robustness.