Study Of MDO Application On Certain Ground-to-Air Missile

Multidisciplinary Design Optimization (MDO) is a new method that developed since last century. Nowadays, there are more and more researches on MDO. After more than two decades development, this method has already been well developed. However, there are still many problems in this method, such as great difficulty between theory and application, which is the research motivatio of this paper. This paper aims at combining the MDO method and the design process of ground-to-air missile.The research work of this paper consists of three parts. The first part is a brief research on MDO technology, the second part is the process of modeling, while the last part is the part of results.In the first part, after a brief overview of the development of MDO and ground-to-air missile, related technologies to MDO and CSSO are discussed, which include the category of MDO method, CSSO and its procedure, Genetic Algorithm and some related theory and Radial Basis Function net-work and some other approximation technology such as Variable Complexity Models, Kriging Method and so on.In the second part, the model for MDO calculation of flight vehicle is discussed and analyzed from the point of system. The aim of this part is to determine the optimization procedure, objective function, design parameters, constraints and son on. After brief discussion, it points out that the MDO method, Concurrent Subspace Design Optimization (CSSO) will be adopted, and Genetic Algorithm (GA) is used to optimize the objective function while Radial Basis Function (RBF) network is used to create approximate model. In the followed part, the models of mass, trajectory, impulsive and aerodynamic are created from the disciplinary view.The third part is the part about the results and discussion on these results. In this part, the figures of some design parameters to related status are listed. Finally, the result of this paper is given. At this status, the objective function of missile improves greatly, which proves the effective and feasibility of CSSO.