Iterative Learning Control for Spacecraft Rendezvous, Proximity Operations, and Docking

The space economy is developing quickly and Canada wants to play a role in the new sector of “in-orbit services”, where satellites are repaired and refueled while space debris is removed from space completely. All these activities require the servicing spacecraft to get a good look at the client spacecraft before docking. In this research, we aim to make the pre-docking inspection orbits as accurate as possible. Through a collaboration between Carleton University and Obruta Space Solutions, we will “learn-by-doing” using Iterative Learning Control (ILC). First developed for factory robotics, ILC will help our servicer learn from position and rotation errors in its first inspection orbit to improve the accuracy of subsequent orbits. These accurate orbits will improve the servicer’s inspection of the client, ultimately increasing the likelihood of a successful servicing mission. Refueling, repairing, and removing — all to help keep space sustainable for generations to come!

Faculty Supervisor:

Steve Ulrich

Student:

Partner:

Obruta Space Solutions

Discipline:

Engineering

Sector:

Manufacturing

University:

Carleton University

Program: