García Martín, JavierAnderson, AlejandroSánchez, Ignacio J.D'Jorge, AgustinaDuviella, ÉricMaestre Torreblanca, José María2024-11-272024-11-272024-06-01García Martín, J., Anderson, A., Sánchez, I.J., D'Jorge, A., Duviella, É. y Maestre Torreblanca, J.M. (2024). Multi-set based model predictive control to explore large freshwater resources. En 3rd IFAC Workshop on Integrated Assessment Modeling for Environmental Systems, IAMES 2024. IFAC-PapersOnLine, Vol. 58, 2 (38-43), Savona: Elsevier.2405-8963https://hdl.handle.net/11441/165008© 2024 The Authors. This is an open access article under the CC BY-NC-ND license.Unmanned surface vehicles can become cutting-edge aquatic laboratories for real-time water quality assessment, evaluating the physical, chemical, and biological profiles of water to detect degradation in freshwater resources. The development of control strategies for surface scanning missions is essential for efficient and effective water resource management. This paper introduces novel exploration methods for analysis experiments. Our approach is founded on an optimizing target-set tracking controller and innovates by adopting a dynamic target-switching method. The target transitions to a further objective once the current target is assured, result in smoother system behavior, as shown by the simulations using the nonlinear model of a commercial surface vehicle tasked with covering a designated area of Heron Lake, located in Villeneuve d’Ascq. The method is implemented in two distinct ways: the first prioritizes passing through all the sets, while the second compromises between passing through and computational cost.application/pdf6 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Coverage ControlEnvironmental MonitoringUnmanned Surface VehicleWater Qualityinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.ifacol.2024.07.088