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Method for optimizing multi-star multitask observation dispatching under complicated constraint condition

A constrained, multi-task technology, applied in the field of deep space exploration, which can solve problems such as incompleteness

Inactive Publication Date: 2015-02-18
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0004] To sum up, the current research on this problem mostly takes maximizing the number of measurement and control tasks as the objective function, but in the actual measurement and control tasks, the influence of task priority on the scheduling results must be considered
Although some scholars have begun to study this issue, the research issues have different emphases and are not yet comprehensive.

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  • Method for optimizing multi-star multitask observation dispatching under complicated constraint condition
  • Method for optimizing multi-star multitask observation dispatching under complicated constraint condition
  • Method for optimizing multi-star multitask observation dispatching under complicated constraint condition

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Embodiment Construction

[0066] The purpose of the present invention is to solve the problem that task priority affects scheduling results in the process of low-orbit spacecraft earth observation scheduling, to study a large-scale multi-task scheduling method with priority under constraints such as timing and resource constraints, and to propose a method Multi-satellite multi-task observation scheduling optimization method under complex constraints.

[0067] The method of the present invention is realized by designing an improved ant colony algorithm (AOC): an ant is used to represent a satellite resource in one circle around the earth (one orbital circle), and the satellite resources in all orbital circles form an ant colony system ; Combined with observation constraints, energy demand estimation and capacity demand estimation are introduced to control the transition probability. Specific steps are as follows:

[0068] 1. Initialize the model parameters of the multi-task and multi-resource schedulin...

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Abstract

The invention relates to a method for optimizing multi-star multitask observation dispatching under a complicated constraint condition and belongs to the technical field of deep space detection. The method is realized by virtue of designing an improved ant colony algorithm; a satellite resource rotating around the earth for one track loop is represented by a satellite, and an ant colony system is formed by all satellite resources in the track loop; in combination of observation restriction, energy demand predication and capacity demand predication are introduced to control the transfer possibility. Restrictions such as time, energy and storage capability are considered in state transition rules, observation dispatching tasks have priority levels, and the method is conductive to improvement of the data collection capability and application level in real satellite task dispatching; the improved ant colony algorithm can be used for converging in a practicable iteration range so as to obtain better solutions.

Description

technical field [0001] The invention relates to an optimization method for multi-satellite and multi-task observation scheduling under complex constraint conditions, and belongs to the technical field of deep space exploration. Background technique [0002] The space dispatching system is responsible for the important task of rationally allocating measurement and control resources and supporting the normal work of spacecraft. At its core is a complex real-time discrete event dynamic system (DEDS), which is essentially a multi-resource, large-scale optimization problem with complex constraints. In recent years, due to the increasing number and types of spacecraft in orbit and planned development, and the measurement and control resources are limited by various restrictions, the contradiction of "more satellites and fewer stations" has become increasingly serious, especially for low-orbit satellites. This problem is particularly acute due to factors such as the large number o...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 徐瑞赵凡宇崔平远李朝玉朱圣英
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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