Research on Semiactive Control of Civil Engineering Structure Based on Neural Network

Abstract

In order to improve the strength of civil engineering structure, a semiactive control model of civil engineering structure based on neural network is proposed, and the control constraint parameter model of semiactive regulation of civil engineering structure is constructed. Combined with the controlled object model, the semiactive control model of civil engineering structure is designed, the mechanical analysis model of civil engineering structure is established, and the semiactive regulation of civil engineering structure is carried out by the small disturbance suppression method. The semiactive adjustment of civil engineering structure is carried out by using the structural strength fusion tracking method. Taking the internal strength and shock yield response of civil engineering structure as constraint parameters, the semiactive control of civil engineering structure is carried out and PID neural network is used to optimize the control system. The simulation results show that the semiactive control of civil engineering structure with this method has good stability, and the strength and yield response strength of civil engineering structure are improved, and it has good control efficiency.