Abstract

Based on structural features of cable-net of deployable antenna, a multiobjective shape optimization method is proposed to help to engineer antenna’s cable-net structure that has better deployment and adjustment properties. In this method, the multiobjective optimum mathematical model is built with lower nodes’ locations of cable-net as variables, the average stress ratio of cable elements and strain energy as objectives, and surface precision and natural frequency of cable-net as constraints. Sequential quadratic programming method is used to solve this nonlinear mathematical model in conditions with different weighting coefficients, and the results show the validity and effectiveness of the proposed method and model.

Highlights

  • Cable-net structure has been widely used in space deployable antenna for light weight, high precision, and small stowed size [1–6]

  • In previous optimization studies for antenna’s cable-net system, many try to find a set of feasible prestresses that can make sure the antenna has the optimum surface precision and dynamic performance; others studied optimization methods that can improve antenna’s surface precision by adjusting lengths of cable elements [7]

  • All these optimization methods are proposed on the same assumption that the antenna has been in its deployment state

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Summary

Introduction

Cable-net structure has been widely used in space deployable antenna for light weight, high precision, and small stowed size [1–6]. In previous optimization studies for antenna’s cable-net system, many try to find a set of feasible prestresses that can make sure the antenna has the optimum surface precision and dynamic performance; others studied optimization methods that can improve antenna’s surface precision by adjusting lengths of cable elements [7]. All these optimization methods are proposed on the same assumption that the antenna has been in its deployment state. Mathematical Problems in Engineering weighting coefficients of objectives to meet different demands for practical necessity

Multiobjective Optimum Mathematical Model
Objectives
An Example
36 Figure 4
Conclusions
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