Active Control of Structures Using Neural Networks

该项目的重点是 开发和测试 结构控制方法 神经网络 研究 活动包括理论 和实验成分。 将进行实验研究 在一个八分之一比例的 九层钢结构 所有 测试将在 美国陆军的摇床 建筑工程研究 实验室（CERL），位于伊利诺伊州香槟尚潘。 CERL技术人员将 参与这个项目。 选择神经网络作为 控制器是重要的 研究的特点是神经 网络具有适合的能力 用于控制应用。 初步实验和 理论研究已经证实 的适用性和力量 神经网络控制 问题 该研究强调两个结构 控制方法，主动支撑 系统和变刚度 方法包括实验 采用新的控制安排。 不同结构控制 设计将被开发， 通过数值模拟研究， 然后将被实施， 在振动台上测试， CERL。 积极响应 控制结构将是 相比之下， 结构不受控制， 没有对角支撑。

The project focuses on the development and testing of structural control methods using neural networks. Research activities include both theoretical and experimental components. Experimental research will be done on a one-eighth scale model of a nine story steel structure. All tests will be performed on the shaking table at the U.S. Army Construction Engineering Research Lab (CERL) at Champaign, Illinois. CERL technical staff will participate in this project. The choice of neural networks as the controller is an important feature of the research as neural networks have capabilities suitable for control applications. Preliminary experimental and theoretical studies have confirmed the applicability and the power of neural networks in control problems. The study emphasizes two structural control methods, active bracing systems and variable stiffness methods including experimentation with new control arrangements. Different structural control designs will be developed and studied in numerical simulations, and then will be implemented and tested on the shaking table at CERL. The response of the actively controlled structure will be compared with the response of the structure without control, with and without diagonal bracing.