Improved sparrow intelligent optimization method based on chaotic mapping and golden sine strategy

Abstract

The invention discloses an improved sparrow intelligent optimization method based on chaotic mapping and golden sine, and aims to solve the problem that the calculation amount is wasted due to the fact that an obtained solution cannot be converged to a globally optimal solution when a reentry trajectory optimization problem of a hypersonic aircraft is solved through the improved intelligent sparrow optimization method. According to the method, a Tent chaos sequence and a reverse elite population strategy are combined to generate an initialized population which is relatively uniform in a solution space; the positions of individuals are updated in a golden sine mode, and the searching step length is controlled through coefficients, so that the individuals are stably close to the optimal positions; the number of mutation individuals is reduced in the later period through a cosine strategy, and the calculation efficiency of later iteration updating is guaranteed; and by utilizing a greedy strategy, when the individuals are updated, the historical optimal positions of the individuals are kept, and the optimization process is accelerated. According to the improved sparrow optimization algorithm, the optimization efficiency is higher, a globally optimal solution can be well obtained, and the problem that local optimum is likely to happen is effectively solved.

Description

technical field [0001] The invention belongs to the field of swarm intelligence optimization algorithms, in particular to an improved sparrow intelligence optimization method based on chaotic mapping and golden sine strategy. Background technique [0002] In recent years, hypersonic aircraft has gradually become an effective tool for implementing global rapid strikes and maintaining air superiority. Generally, an aircraft that can fly at a speed of more than 5 times the speed of sound is defined as a hypersonic aircraft. This type of aircraft has better aerodynamic performance and large airspace. Therefore, it has very good application prospects in both military and civilian fields. The re-entry process refers to the process in which a hypersonic vehicle re-enters the atmosphere from outside the Earth's atmosphere and lands at a very fast speed. However, the complex environment and uncertainties bring great challenges to the realization of re-entry trajectory planning. [0...

AI Technical Summary

Problems solved by technology

Among them, the sparrow search algorithm is a new type of swarm intelligence optimization algorithm proposed in 2020. Compared with other optimization algorithms, it has the advantages of high search accuracy, fast convergence, and high stability. There is a problem that the calculation efficiency in the later stage of the algorithm is high, and it is easy to fall into the local optimal solution. In this way, when the sparrow optimization algorithm is used to solve the hypersonic vehicle reentry trajectory optimization problem, the obtained solution will not converge to the global optimal solution, resulting in calculation amount of waste

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