Active Control of Structures Using Neural Networks and Fuzzy Logic

9503209 Ghaboussi该项目继续并扩展了伊利诺伊大学研究人员于1992年根据国家科学基金会的结构控制程序使用神经网络开发的主动结构控制方法。在新的结构控制方法中，主控制器是经过训练的神经网络，称为神经控制器。神经控制器的训练是在仿真器神经网络的帮助下完成的，该仿真器神经网络首先被训练来学习结构的行为。数值仿真结果表明，与其他控制方法相比，新的结构控制方法具有更强的鲁棒性，是一种固有的自适应控制器。在本项目中，基于神经网络的结构控制方法的研究将继续包括：(1)新结构控制方法的实验验证；(2)扩展到非线性控制问题。实验工作将分两个阶段进行。在初始阶段，将对仿真器神经网络和神经控制器进行广泛的试错、调整和在线训练。验证测试将在伊利诺伊大学结构工程实验室的振动台上进行，使用与数值模拟中使用的类似的三层一跨结构模型。下一阶段的实验工作将在NCEER设施中进行，建立一个更大的结构模型。最后，必须推广新的结构控制方法，以解决结构遭受不可预测损伤的非线性控制问题，并发展一种可行的、实用的结构非线性控制方法。***

9503209 Ghaboussi This project continues and extends the development of an active structural control method using neural networks by the investigators at the University of Illinois in 1992 under the NSF's structural control program. The main controller in the new method of structural control is a trained neural network, referred to as the neuro-controller. The training of the neuro-controller is accomplished with the aid of an emulator neural network, which is first trained to learn the structural behavior. Results from the numerical simulations showed that the new structural control method performs well compared to other control methods and is far more robust as well as being an inherently adaptive controller. In this project research on neural network based methods of structural control will be continued to consist of (1) experimental verification of the new structural control method; and (2) the extension into nonlinear control problems. The experimental work will be done in two stages. In the initial stage, extensive trial and error, adjustment and the online training of the emulator neural network and the neuro-controller will be done. Verification tests will be conducted on the shaking table at the University of Illinois Structural Engineering Laboratory, using a three story, one bay structural model, similar to those used in numerical simulations. The next stage of experimental work will be conducted at the NCEER facilities, on a larger structural model. Finally, the new method of structural control must be extended to address the problem of nonlinear control of structures sustaining unpredictable damage and develop a feasible and practical method of nonlinear structural control. ***