@article{6a96521d-575d-4c7c-8f13-a458d89ac02f,
  abstract     = {{Explicit solutions to optimal control problems are rarely obtainable. Of particular interest are the explicit solutions derived for minimax problems, providing a frame work to address adversarial conditions and uncertainty. This work considers a multi-disturbance minimax Linear Regulator (LR) framework for positive linear time-invariant systems in continuous time, which, analogous to the Linear-Quadratic Regulator (LQR) problem, can be utilized for the stabilization of positive systems. The problem is studied for nonnegative and state-bounded disturbances. Dynamic programming theory is leveraged to derive explicit solutions to the minimax LR problem for both finite and infinite time horizons. In addition, a fixed-point method is proposed that computes the solution for the infinite horizon case, and the minimum L1-induced gain of the system is studied. We motivate the prospective scalability properties of our framework with a large-scale water management network.}},
  author       = {{Gurpegui Ramón, Alba and Jeeninga, Mark and Tegling, Emma and Rantzer, Anders}},
  issn         = {{1558-2523}},
  language     = {{eng}},
  month        = {{03}},
  pages        = {{1--1}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Automatic Control}},
  title        = {{Minimax Linear Regulator Problems for Positive Systems}},
  url          = {{http://dx.doi.org/10.1109/TAC.2026.3673160}},
  doi          = {{10.1109/TAC.2026.3673160}},
  year         = {{2026}},
}