| This paper focuses on a research on the optimization design method for Super Range Guided Rocket trajectory based on genetic algorithm.Since the select of the trajectory scheme has a great impact on the performance of Super Range Guided Rocket, it is necessary to optimize the trajectory.However, a suitable optimization method should be chosen due to the nonlinear optimization problem with complicated constraints in the trajectory optimization. As there are some disadvantages to deal with the above mentioned optimization problem in common methods, genetic algorithm will be implemented in this paper.First of all, a simplified trajectory optimization model is established based on the simplification of 6-DOF trajectory mathematical model of Super Range Guided Rocket body. Then a hybrid numerical algorithm combining Adams and Range-Kutta algorithms is used to solve the differential equations.Two improved genetic algorithms are proposed to overcome the disadvantages of the current genetic algorithm. One is based on niche technique while the other is based on hierarchical architecture and elitist preserved strategy. The proposed genetic algorithms are validated to restrain the prematurity effectively through the testing function. Hence the proposed algorithms are suitable to solve the optimization problem with multimodal functions. One of the proposed genetic algorithms is determined to solve the trajectory optimization problem in terms of the comparison of the two proposed algorithms.The mathematical models for Super Range Guided Rocket trajectory optimization design of XX-A and XX-B are established. Then the proposed genetic algorithm is used to deal with the optimization design. The design tasks including definition of objective function, choice of design parameters, processing method of constraints, and analysis of the calculated results are achieved.The methods proposed in this paper will offer a good reference to the further research and development of the related products... |
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