Abstract
The structural identification and dynamic control of a cable-stayed bridge are considered to be difficult due to the structural complicacy and system uncertainties. In this paper, based on the concept of decentralized information structures, a decentralized non-parametric identification and control method is proposed with neural networks for the purpose of suppressing the vibration of a well-studied and documented two-cable-stayed bridge induced by earthquake excitations. The control strategy proposed here uses the stay cables as active tendons to provide control forces through appropriate actuators. Each individual actuator is controlled by a decentralized neuro-controller that only uses local velocity and relative displacement information. The feature of decentralized control simplifies the implementation of the control algorithms and makes decentralized control easy to practice and cost effective. The effectiveness of the decentralized identification and control algorithm is evaluated through numerical simulations. The performance of the decentralized control is compared with that of the linear decentralized control method. And the adaptability of the decentralized neuro-controllers for different kinds of earthquake excitations is demonstrated via simulations.
