Design of a guided missile interceptor using a genetic algorithm

An apportioned pareto genetic algorithm was used to manipulate a solid rocket design code, an aerodynamic design code, and a three-loop autopilot to produce guided missile interceptor designs capable of accurately engaging a high-speed/high-altitude target. Definition of the optimization problem required 29 design variables, and 4 primary goals were established to assess the performance of the interceptor designs. Design goals included the following: minimize miss distance, minimize intercept time, minimize takeoff weight, and minimize maximum g loading. In 50 generations, the genetic algorithm was able to develop 2 basic types of external aerodynamic designs that performed nearly the same, with miss distances less than 1.0 ft. The solid rocket motors that propelled these external shapes shared common characteristics such as a large initial burning area and a large combustion chamber volume. The genetic algorithm did not prefer maximizing the amount of fuel within the rocket motor case thigh fuel volume ratio). A higher fuel volume ratio typically means higher launch weight, but does not necessarily guarantee faster intercepts given finite thermal limits. Examination of the intercept trajectories themselves shows that standard proportional navigation guidance works adequately, but could probably be improved by thrust compensation, especially during the launch transient. The three-loop autopilot performs well even for high-altitude engagements, and the analytic gain determination makes the autopilot straightforward to implement.