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Trajectory fast optimization method and apparatus based on gradient particle swarm algorithm

A particle swarm algorithm and optimization method technology, which is applied in the directions of instruments, adaptive control, control/regulation systems, etc., can solve problems such as inability to optimize ballistics, and achieve the effects of high efficiency, fast search speed, and high convergence accuracy.

Inactive Publication Date: 2018-01-16
中国人民解放军火箭军研究院 +1
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Problems solved by technology

[0006] The present invention provides a trajectory fast optimization method and device based on gradient particle swarm algorithm, electronic equipment and computer-readable storage medium to solve the problem in the prior art that the trajectory cannot be optimized efficiently and with high precision

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  • Trajectory fast optimization method and apparatus based on gradient particle swarm algorithm
  • Trajectory fast optimization method and apparatus based on gradient particle swarm algorithm
  • Trajectory fast optimization method and apparatus based on gradient particle swarm algorithm

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Embodiment 1

[0051] refer to figure 1 , shows a flow chart of the steps of a method for fast ballistic optimization based on the gradient particle swarm optimization algorithm according to an embodiment of the present invention.

[0052] The ballistic rapid optimization method based on the gradient particle swarm algorithm of the present embodiment comprises the following steps:

[0053] Step 101: Initialize the k-th generation population and the k-1th generation population, and determine the first global optimal individual corresponding to the k-th generation population, and the second global optimal individual corresponding to the k-1th generation population .

[0054] Among them, the kth generation population is the current generation population and the latest generation population, and the k-1th generation population is the next generation population.

[0055] When the population is initialized, the position vector and velocity vector of all or individual particles in the population ...

Embodiment 2

[0064] refer to figure 2 , shows a flow chart of the steps of a method for fast ballistic optimization based on the gradient particle swarm optimization algorithm according to Embodiment 2 of the present invention.

[0065] In the basic particle swarm optimization algorithm, the particles update their position vector and velocity vector by tracking the individual optimal solution and the global optimal solution. This process makes the global search ability of the particle swarm iteration in the early stage and the local search ability in the later iteration weak. The present invention takes this embodiment as an entry point, integrates the idea of ​​gradient search into the particle swarm algorithm, and proposes a new gradient particle swarm optimization algorithm. The algorithm uses the global optimal value of the k-1 generation population and the k-th generation population to generate the search gradient, and then realizes the efficiency of the particle swarm search based o...

Embodiment 3

[0093] refer to image 3 , showing a flow chart of the steps of a method for fast trajectory optimization based on the gradient particle swarm algorithm according to the third embodiment of the present invention.

[0094] In the embodiment of the present invention, the missile shooting accuracy is taken as the objective function, and on the basis of designing the missile flight program and establishing the ballistic optimization model, the gradient particle swarm algorithm is used to study the ballistic missile ballistic planning problem to quickly optimize the missile ballistic.

[0095] The missile flight program is designed as follows:

[0096] The ballistic missile completes the missile flight mission through the primary power flight section, the secondary power flight section, the free flight section and the reentry flight section. During this process, the missile flies according to the standard ballistic trajectory, and its motion attitude changes with the change of the...

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Abstract

The embodiment of the invention provides a trajectory fast optimization method and apparatus based on a gradient particle swarm algorithm. The trajectory fast optimization method based on the gradientparticle swarm algorithm includes the steps: initializing the kth generation of population and the k-1th generation of population, and determining the first global optimal individual corresponding tothe kth generation of population and the second global optimal individual corresponding to the k-1th generation of population; determining whether the fitness value of the first global optimal individual is greater than the fitness value of the second global optimal individual; if not, on the basis of taking the position vector corresponding to the first global optimal individual as the startingpoint, generating the k+1th generation of population, according to the k+1th generation of population and the kth generation of population, performing trajectory optimization; and if so, utilizing thegradient method to update the position vector corresponding to the first global optimal individual, taking the position vector corresponding to the first global optimal individual as the starting point, generating the k+1th generation of population, and according to the k+1th generation of population and the kth generation of population, performing trajectory optimization. The trajectory fast optimization method and apparatus based on a gradient particle swarm algorithm can realize fast optimization of trajectory.

Description

technical field [0001] The present invention relates to the technical field of aircraft design, in particular to a method and device for rapid trajectory optimization based on a gradient particle swarm algorithm, an electronic device and a computer-readable storage medium. Background technique [0002] Ballistic optimization is an important part of the overall optimization design of ballistic missiles, which runs through the whole process of missile design and combat application. Ballistic optimization refers to the process of optimally selecting the trajectory of the missile from the starting point to the target point that satisfies a certain performance index under certain specific constraints. From a mathematical point of view, the ballistic optimization problem is an optimal control problem with state constraints, path constraints and control constraints under nonlinear conditions. The methods for solving optimal control problems mainly include indirect methods, direct ...

Claims

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Application Information

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IPC IPC(8): G05B13/04
Inventor 孙向东刘刚徐军李振华饶颖何兵胡琛秦伟伟盛兵
Owner 中国人民解放军火箭军研究院
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