Optimization of structural parameters for space deployable truss antenna with multi-module

In order to reduce the launching cost of deployable antenna and improve its deployment stiffness, by taking the mass and the first order natural frequency of deployable truss antenna with multi-module as the objective functions, the structural parameters of truss structure were optimized based on BP (back propagation) neural network and genetic algorithm. The numerical simulation of structural parameters was studied by software ANSYS, and the objective function values corresponding to the design variables were obtained. The training samples and test samples were obtained by orthogonal design. According to the basic idea of BP neural network, prediction model was derived by adjusting the parameters of network model. Sub-goals multiplication and division were adopted to simplify the multi-objective optimization as a single-objective function. The optimization analysis was performed by genetic algorithm, and the design parameters of truss structure were obtained. The results show that the mass is reduced and the deployment stiffness is improved simultaneously. This optimization method provides a foundation for the structural design of deployable truss antenna.