Model predictive control for spacecraft rendezvous and docking with uncooperative targets - Burak, Iskender Omer (Nanyang Technological University, 2020)
This thesis develops guidance & control strategies for rendezvous and docking with uncooperative targets in space. The past and current state of art for rendezvous missions are capable of docking with stable and cooperative targets. However, future applications will require full autonomy on-board, robustness to the changing environments and explicit handling of constraints due to the absence of communication with potential targets. In our approach, we employ Model Predictive Control (MPC) paradigm that generates a set of control inputs and the resulting predicted states to optimize performance objectives while respecting the dynamic and physical constraints. Only the first set of inputs are implemented and based on the new states, the optimization is repeated as the spacecraft moves. Moreover, Guidance and Control (G&C) blocks are unified via the MPC paradigm and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. The design of the G&C controller is formulated as a convex optimization problem where constraints such as thruster limits are explicitly handled. The proposed strategy allows safe and fuel-efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. The proposed controllers are evaluated in a High Fidelity Engineering Model (HFEM) in simulation, and are validated with Hardware-In-The-Loop (HIL) experimental results. Because MPC implementation relies on finding in realtime the solution to constrained optimization problems, computational aspects are also examined and the gap is addressed via experiments in a “zero-G” (air cushion) environment with real sensors, actuators, and on-board processor. This thesis concludes that the proposed dual quaternion based MPC paradigm is a promising framework for the crossroads of future space applications.