A Desensitized Trajectory Optimization Method for Landing of Small Bodies

Abstract

A desensitized trajectory optimization method was proposed to improve the precision of small body landing control in complex environments, under the influence of the uncertainty of dynamic parameters and state during small body landing. Firstly, considering the influence of uncertain parameters, the augmented stochastic state equation of small body landing was established, and the uncertainty of the gravitational field of small body and the thrust error of probe engine were regarded as the process noise of landing process. Then, the linear covariance dynamic equation of uncertainty propagating along the nominal trajectory was derived, the covariance matrix of state variables was extended to a new state of the state equation, and the joint performance index weighted by fuel consumption and state covariance was constructed. Then the optimal control problem was solved by direct trajectory optimization method and the trajectory’s desensitization was finally improved. Taking 433Eros as an example, the simulation results show that the proposed method can overcome the influence of random parameters in the process of small body landing and improve landing accuracy.

Keywords

small body landing / trajectory optimization / desensitization / linear covariance