Deformation control of piezoelectric intelligent curved shell structure with multiple actuators based on neural network optimized by genetic algorithm
Year: 2024
Type: article
Abstract: In aerospace engineering, it is important to achieve precise deformation control of curved shell. In this paper, the piezoelectric intelligent curved shell structure (PICSS) with multiple actuators was selected as the research object. Firstly, a finite element model of the structure was constructed, and the sample data was obtained based on simulation method for the back propagation (BP) neural network. Next, the structure of the BP neural network was determined as ‘6–13-24-3′ with the goal of obtaining the minimum mean square error. Then genetic algorithm was used to optimize the initial weights and thresholds of the BP neural network, and the input voltage of each actuator was predicted. The accuracy of voltage prediction was confirmed through collaborative simulation technology by testing the BP neural network before and after optimization. Finally, the deformation perception and control of the piezoelectric curved shell were verified through the PICSS.
Source: Measurement
Authors: Xining Li, Shiqi Song, Yuzhi Liu
Institution: Northwestern Polytechnical University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,650
OpenAlex ID: W4403728530