Research On Optimization Algorithms For Aerodynamic Parameter Identification Of Rocket Projectiles

Aerodynamic parameter identification,as a key foundational technology in missile testing and design,is of great significance in studying the flight characteristics of missiles.In aerodynamic parameter identification,if optimization algorithms can be used to quickly and effectively identify important parameters,it will play a very important role in model design and performance improvement.Based on the establishment of the six degrees of freedom mathematical model and the nonlinear aerodynamic modeling of the rocket,this paper uses the optimal input technology to input excitation to the parameter identification system,and studies the aerodynamic parameter identification and its optimization algorithm.Firstly,according to the aerodynamic characteristics and motion characteristics of rockets,the relevant coordinate system is defined,the six degrees of freedom flight dynamics model is established,and the polynomial aerodynamic model is established to facilitate the subsequent research on aerodynamic parameter identification.Secondly,by using the optimal input design technique to optimize and modify the relevant parameters in the input excitation,the identification performance indicators of the system can achieve optimal results,and the evaluation criteria of the optimal input design can be used as an evaluation of the accuracy of aerodynamic parameter identification results.Therefore,optimizing the input excitation based on the optimal design criteria can provide a foundation for subsequent research on aerodynamic parameter identification.Then,analyze and study the identification methods of aerodynamic parameters.By comparing and analyzing the Newton-Raphson optimization algorithm based on maximum likelihood method and genetic algorithm,genetic algorithm was chosen to identify the aerodynamic parameters studied.Based on its slow convergence speed and its tendency to fall into local optima,an improved genetic algorithm is proposed,which combines a hybrid improvement selection strategy with simulated annealing algorithm to guide the idea of crossover and mutation strategies,and adopts an elite individual retention strategy to enhance its global convergence ability,thus providing the possibility of its application in rocket aerodynamic parameter identification.Finally,the nonlinear aerodynamic identification model of the rocket is established based on the six degrees of freedom mathematical model of the rocket,and the input excitation designed by the optimal design criteria is used as the system input.The improved genetic algorithm is applied to the optimization algorithm of the rocket aerodynamic parameter identification,and its aerodynamic parameters are identified.The identification results are compared with the results of the traditional identification algorithm and the standard genetic algorithm,and the accuracy evaluation is made,The results indicate that the improved genetic algorithm can be effectively applied to the identification of rocket aerodynamic parameters.