Reentry trajectory optimization method based on immune clone selection

Abstract

The invention belongs to the technical field of guidance control, and discloses a reentry trajectory optimization method based on immune clone selection, which is suitable for seeking a flight trajectory enabling a specified performance index to reach the optimal when a high-speed aircraft reenters the atmosphere. The method comprises the following implementation steps: constructing an aircraft reentry trajectory optimal control problem; discretely parameterizing the aircraft reentry trajectory optimal control problem into a nonlinear programming problem; solving the nonlinear programming problem by adopting an immune clone selection algorithm to obtain a suboptimal solution of the nonlinear programming problem; and taking the suboptimal solution as an initial estimation solution, and solving a nonlinear programming problem by adopting a sequential quadratic programming method to obtain the optimal reentry trajectory of the aircraft. According to the method, the suboptimal solution obtained by the immune clone selection algorithm is used as the initial estimation solution of the sequential quadratic programming method, so that tedious artificial design and initial value tests are avoided, the convergence rate of solution of the sequential quadratic programming method is increased, and the precision is further improved by virtue of the sequential quadratic programming method.

Description

technical field [0001] The invention belongs to the technical field of guidance and control, in particular to a reentry trajectory mixing optimization method based on immune clone selection. Background technique [0002] The motion trajectory of the center of mass of the aircraft from a certain re-entry point at the boundary of the atmosphere to the predetermined landing point without thrust is called the re-entry trajectory. Reentry trajectory optimization has very important significance and engineering value. Through trajectory optimization, a reentry trajectory with better performance can be designed to achieve performance indicators such as maximum range and minimum heating, which can improve the mission execution capability of the aircraft. As one of the key technologies to guide the aircraft to reach the landing point accurately, so as to complete the recovery, the research on the solution method of the aircraft re-entry trajectory optimization problem has become a ho...

AI Technical Summary

Problems solved by technology

Sequential quadratic programming algorithm is currently the best gradient optimization algorithm. Although it has good local optimization ability and is widely used, it still has the common defect of gradient optimization algorithm that is sensitive to the initial estimated solution. When the initial estimated solution When it is poor, it takes a long time to solve

[0005] The second prior art discloses an immune clone selection algorithm, which belongs to an intelligent optimization method and has low sensitivity to the initial estimated solution, but its local optimization ability is poor, and the optimization efficiency and solution accuracy in the later stage of the algorithm iterative solution are relatively low. Low

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