Cooperative planning method of spacecraft attitude and orbit based on chaotic population mutation pio

Abstract

The invention discloses a spacecraft attitude and orbit collaborative planning method based on chaotic population variation pigeon-inspired optimization (PIO), and belongs to the technical field of satellite attitude and orbit control. According to the spacecraft attitude and orbit collaborative planning method, the pigeon dynamic optimization strategy of exploring, searching, variation and homingis adopted at the evolution stage of an algorithm; at the map compass stage, initialization operation is conducted by adding chaotic operators aiming at the population initialization problem, after the population is initialized, adaptive operators are added, and thus the population can evolve in an adaptive mode according to the current population evolution state, and meanwhile the problem that the population is caught in the local optimal solution is solved by adding mutation operators; and at the landmark operator stage, contracting operators are added aiming at the problem of population contracting, the problems that superior individuals run away too fast, and the population degenerates are solved, thus the planning result is smoother, population evolution is deeper, the local optimalsolution problem and the algorithm divergence problem are solved, and the calculated quantity of the algorithm is further reduced.

Description

technical field [0001] The invention discloses a collaborative planning method for spacecraft attitude and orbit based on chaotic population variation PIO, and belongs to the technical field of satellite attitude and orbit control. Background technique [0002] The PIO (Pigeon-Inspired Optimization) algorithm is inspired by the navigation process of the pigeons in the homing process. When the pigeons are far away from the destination, they mainly rely on the sun and geomagnetism for navigation. Landmarks will be used for navigation after arriving at the destination, and individuals in the group who are not familiar with the landmarks will follow the group that is familiar with the landmarks. [0003] The existing PIO algorithm can realize obstacle avoidance, path planning, and image edge recognition of UAVs and robots, but it has not yet solved the problem of coordinated planning of spacecraft attitude orbits under complex constraints and strong coupling relationships. The ...

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Problems solved by technology

[0006] The purpose of the invention of the present invention is to address the deficiencies of the above-mentioned background technology, providing a collaborative planning method for spacecraft attitude orbit based on chaotic population variation PIO, adopting the improved PIO algorithm to realize the collaborative planning of spacecraft attitude orbit under strong coupling relationship, solving The existing spacecraft attitude and orbit planning schemes have not yet realized the coordinated planning of attitude and orbit, and the existing attitude planning schemes or orbit planning schemes do not consider all dynamic constraints and all factors that affect the planning results, and the technical problems of high complexity

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