Rapid, Robust Trajectory Design Using Indirect Optimization Methods

Abstract

An efficient methodology is created to formulate robust trajectory design problems within an indirect optimization framework. An augmented cost functional is used to capture the worst case scenario associated with each modeled dispersion. This approach eliminates the need to propagate statistical information, thereby minimizing the dimension of the design problem. The proposed methodology enables robustness considerations to be directly incorporated into the optimization problem in which the mathematical information associated with indirect methods is used to provide explicit interaction information among nominal and dispersed trajectories. Examples illustrate the ability to construct highly coupled, complex solutions that capture all of the robustness considerations of interest to the designer. This approach enables the rapid construction of families of solutions that trade performance and robustness based on designer preference.