Richard Zappulla

Dynamic Air-Bearing Hardware-in-the-Loop Testbed to Experimentally Evaluate Autonomous Spacecraft Proximity Maneuvers

Ground-based testbeds are critical to develop and test different elements of spacecraft guidance, navigation, and control subsystems. This paper provides an in-detail description of a state-of-the-...

Analysis and Experimentation of Model Predictive Control for Spacecraft Rendezvous and Proximity Operations with Multiple Obstacle Avoidance

In this paper, Model Predictive Control (MPC) approaches are applied to multiple obstacle avoidance maneuvers for spacecraft rendezvous and docking. For safe obstacle avoidance, keep-out constraints are introduced by bounding ellipsoids around obstacles. In a linear quadratic MPC (LQ-MPC) framework, the rotating hyperplane method is used to convexify the obstacle avoidance constraints. A new method using two hyperplanes for convexification of the constraints is also proposed to improve performance of the LQ-MPC approach. A nonlinear MPC (NMPC) approach that deals with the nonlinear obstacle constraints directly is also applied to solve the spacecraft proximity maneuvering problems by using the nonlinear programming solver IPOPT (Interior Point OPTimizer). Real-time implementation of the MPC solutions is analyzed and compared on a physical test bed using several test cases. Numerical simulations and experiments demonstrate the obstacle avoidance as well as real-time operation capabilities of the considered control approaches.