Flores Campos, Juan AlejandroPerrusquía, Adolfo2024-01-042024-01-042023-12-05Flores-Campos JA, Perrusquía A. (2023) Robust control of linear systems: a min-max reinforcement learning formulation. In: 2023 20th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 25-27 October 2023, Mexico City, Mexico979-8-3503-0677-42642-3774https://doi.org/10.1109/CCE60043.2023.10332826https://dspace.lib.cranfield.ac.uk/handle/1826/20610In this paper, an online robust controller based on a min-max reinforcement learning approach for linear systems is discussed. Disturbances are represented by external signals coupled with the control input which are assumed to be bounded within a set of admissible disturbances. The proposed controller implements a min-max approach which realizes a smooth transition between optimal and robust controllers. Lyapunov stability theory is used to assess the stability and boundedness of the min-max robust formulation. A neural reinforcement learning architecture is used to obtain an approximation of the parameters associated to the optimal cost. Simulations are carried out to validate the proposed approach.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/Conference paper979-8-3503-0676-72642-3766