Active Control of Structures Using Neural Networks

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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.