Hierarchical Decentralized Control of Building Structure based on Genetic Algorithm and BP Neural Network

With the continuous improvement of design theory, the improvement of the durability of building materials and the progress of construction technology, many super large buildings have appeared. These buildings are important buildings related to the national economy and people's lives. As the scale of the building increases, some of the performance of the structure will also change accordingly. For example, the rigidity and resistance of the structure will be significantly reduced, and the dynamic response of the structure will become very large, resulting in earthquake deterioration and reduced construction safety and reliability. Therefore, it is necessary to improve the operation and safety of building structures through structural control methods that effectively resist external loads. Because the large-scale building structure control system is a high-dimensional control system, the control of the structure becomes more complicated, and the decentralized control is very suitable for solving the control problems of this type of building structure. In this paper, the decentralized control method is introduced into the vibration control of the building structure, and the BP decentralized control method is used to study the structural vibration control with the integrated structure as the object to verify the effectiveness of the decentralized control method in the control of the building structure; the genetic algorithm is used to realize the construction of the structure. Hierarchical decentralized control, while obtaining optimal control parameters, and meeting the expected control performance indicators of the closed-loop system.