【摘要】 抖振问题是离散滑模控制在实际系统中应用的突出障碍.根据神经网络控制的优点,采用一种基于RBF神经网络的离散滑模控制方法对地震作用下建筑结构的振动控制问题进行了研究.根据离散系统建模技术,得到了离散时间形式的状态方程,同时给出了确定切换面的方法,并推导了控制律的表达式.以一个三层剪切型建筑结构模型为例来验证所提出的离散滑模控制方法的有效性.算例分析结果表明:本文所提出的控制方法能够有效地减小结构的地震峰值响应,同时达到了削弱控制系统抖振的目的.更多还原

【Abstract】 Based on the advantage of RBF neural network control method,a new discrete-time adaptive sliding mode control method,which is one of the active control algorithms,was applied for seismically excited building structures.The undue chattering effect and the major disadvantage of conventional sliding mode controller have been removed by introducing RBF neural network controller to suppress parameter vibrations and perturbations greatly.This paper proposed several ways to get the switch surface and to design the feedback controller.For numerical application,a three-story shear building model subjected to ground excitations was considered.The ground accelerations recorded in two different earthquake events were used to evaluate the effectiveness of the control algorithm for varied disturbances.The simulation results show preliminarily that our new discrete-time adaptive sliding mode control method is quite effective:not only can it reduce the peak-response of the ground motion,but also it can keep the chattering effect sufficiently low so as to ensure the system stable.更多还原