@article{flus2023distributed,
  abstract = {This paper proposes a method to control a class of multi-agent systems with uncertainties modeled as stochastic processes with arbitrary probability distributions. The considered control problem is to lead a formation of agents through a space which is partially obstructed by obstacles. The proposed solution is to use a hierarchically structured approach of distributed stochastic model predictive control (DSMPC). The approach combines elements of formation reference structures, leader-follower concepts, and successive convexification (SC) for collision avoidance. To consider the stochastic uncertainties, over-approximated probabilistic reachable sets (PRS) are computed based on Chebyshev's inequality. The nominal (expected) agent behavior is optimized within the DSMPC such that (probabilistic) constraints are satisfied in a distributed way. For the overall approach, closed-loop stability of the distributed control concept is investigated and an illustrating example is provided.},
  author = {Flüs, P. and Stursberg, O.},
  doi = {https://doi.org/10.1016/j.ifacol.2023.10.890},
  interhash = {62aa14ef15ed5d70f97cc177c44c8cac},
  intrahash = {2cd0138f1a4936e5143c16df439c6588},
  journal = {Proc. of the 22nd IFAC World Congress},
  number = {Issue 2},
  pages = {10155-10161},
  title = {Distributed MPC of Uncertain Multi-Agent Systems Considering Formations and Obstacles},
  url = {https://www.sciencedirect.com/science/article/pii/S2405896323012715},
  volume = {Volume 56},
  year = 2023
}