RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks

@article{Brunke2021RLOMPCRL,
  title={RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks},
  author={Lukas Brunke and Siqi Zhou and Angela P. Schoellig},
  journal={2021 60th IEEE Conference on Decision and Control (CDC)},
  year={2021},
  pages={2183-2190}
}
In this work we address the problem of performing a repetitive task when we have uncertain observations and dynamics. We formulate this problem as an iterative infinite horizon optimal control problem with output feedback. Previously, this problem was solved for linear time-invariant (LTI) system for the case when noisy full-state measurements are available using a robust iterative learning control framework, which we refer to as robust learning-based model predictive control (RL-MPC). However… 

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