Data-driven Distributionally Robust MPC: An indirect feedback approach [article]

Christoph Mark, Steven Liu
2021 arXiv   pre-print
This paper presents a distributionally robust stochastic model predictive control (SMPC) approach for linear discrete-time systems subject to unbounded and correlated additive disturbances. We consider hard input constraints and state chance constraints, which are approximated as distributionally robust (DR) Conditional Value-at-Risk (CVaR) constraints over a Wasserstein ambiguity set. The computational complexity is reduced by resorting to a tube-based MPC scheme with indirect feedback, such
more » ... at the error scenarios can be sampled offline. Recursive feasibility is guaranteed by softening the CVaR constraint. The approach is demonstrated on a four-room temperature control example.
arXiv:2109.09558v1 fatcat:kbshmr3w7fcbtgsubfqek664l4