Optimization method for processing multiple extreme values and multiple restricted problems in flight vehicle design

Abstract

The invention discloses an optimization method for processing multiple extreme values and multiple restricted problems in flight vehicle design, relates to an optimization method of multiple extreme values and multiple restricted problems in processing flight vehicle design, and belongs to the field of flight vehicle design optimization. The optimization method combines a filter principle and a particle cluster optimization, forms a design method with ability of processing global optimization, realizes the data processing and solution of multiple extreme values and multiple restricted problems in the flight vehicle design, ensures the understanding feasibility, avoids the repeated work of setting penalty factors in traditional design solution, and improves the design efficiency and solving precision. The data processing and solving process of the optimization method is separated from a flight vehicle design optimization model, thus the universality of the optimization method is increased. The optimized design result under the conditions of multiple extreme values and multiple restrictions is applied to the flight vehicle project design; the optimization method is indirectly possessed of the advantages of shortening the design cycle of the flight vehicle, reducing cost and consumable items of appointed design task, and realizes the improvement of comprehensive performance of the flight vehicle in the appointed design task.

Description

technical field [0001] The invention relates to an optimization method for dealing with multi-extreme and multi-constraint problems, in particular to an optimization method for processing multi-extreme and multi-constraint problems in aircraft design, belonging to the field of aircraft design optimization. Background technique [0002] Today, many aircraft engineering design examples can be attributed to function optimization problems, and engineering applications often contain constraints. Therefore, it is of great significance to study the solution method of constrained optimization problems and form a set of feasible data processing schemes to guide the actual engineering design problems. practical significance. In order to make the design results meet the problem constraints, the penalty function method, sequential quadratic programming and feasible direction method are generally used to deal with the problem constraints at home and abroad. The latter two methods need t...

AI Technical Summary

Problems solved by technology

[0018] The technical problem to be solved by the present invention is to realize the high-precision and low-time-consuming solution of the optimal design of the aircraft design under the condition of multi-extreme values ​​and multi-constraints.

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