Optimal Control of Seismic Response of Structures

我们开发了一种新的闭环开环最优控制律，已通过最小化的二次时变性能指标和动态能量输入到结构系统的总和。考虑了三种输入能量，即地震能量、控制力能量和两者之和。由于控制力不依赖于结构系统的刚度，因此该控制律简单可靠，便于在线控制。详细研究了性能指标中两个加权矩阵对控制效率的影响。利用神经网络的概念，我们已经开发了一种算法来实现开发的控制律到结构系统控制结构的地震反应。该算法由两部分组成。一种是应用反向传播学习过程辨识结构参数，如质量、阻尼和刚度矩阵的辨识模式。另一种是控制器模式，在该模式中，由响应和控制力向量以及输入到结构系统的地震能量组成的时变性能指标最小化。为了实现一个实用的控制装置的主动质量阻尼器（AMD）类型的高层建筑，我们也实施了这种新的算法到一个八层的建筑模型与AMD系统和检查的可行性，以控制结构的地震反应。数值算例验证了所提算法的有效性。

We developed a new closed-open-loop optimal control law that has been derived by minimizing the sum of the quadratic time-dependent performance index and the dynamic energy input to the structural system. Three types of input energy are considered that are the seismic energy, control force energy and the sum of both energy. This control law is simple and reliable for on-line control operations because control force does not depend on the rigidity of structural system. The control efficiency affected by two weighting matrices included in the performance index is investigated in detail. Using the concept of neural network we have developed an algorithm to implement the developed control law into structural system for controlling seismic response of structures. The algorithm consists of two parts. One is an identification mode in which the back propagation learning process is applied to identify the structural parameters such as mass, damping and stiffness matrices. The other is a controller mode in which the time-dependent performance index consisting of response and control force vectors as well as the seismic energy input to the structure system is minimized. To realize a practical control device of active mass damper (AMD) type for high-rise buildings we also implemented this new algorithm into an eight story building model with AMD system and checked feasibility to control seismic response of the structure. Numerical examples are worked out to demonstrate the control efficiency of the proposed algorithms.