Anderson, AlejandroGarcía Martín, JavierBouraqadi, NouryEtienne, LucienFabresse, LucLangueh, Kokou A.A.Lozenguez, GuillaumeRajaoarisoa, Lala H.Maestre Torreblanca, José MaríaDuviella, Éric2023-04-282023-04-282022Anderson, A., García Martín, J., Bouraqadi, N., Etienne, L., Fabresse, L., Langueh, K.A.A.,...,Duviella, É. (2022). Map Meshing Impact on the Efficiency of Nonlinear Set-based Model Predictive Control for Water Quality Assessment. En 2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022, IFAC-PapersOnLine, 55 (33) (105-110).2405-8963https://hdl.handle.net/11441/144885This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)Unmanned Surface Vehicles (USVs) are used to collect data of physicochemical parameters used to determine the degradation of freshwater resources. An optimal strategy based on a Nonlinear set-based Model Predictive Control (NMPC) is designed to improve the control of the USVs. This work offers a theoretical novel formulation of NMPC and explains the interest of set-based NMPC. The influence of meshing the map of the area of interest is then studied and it is finally demonstrated that complex trajectories, i.e. spiral or u-turn or even exploring in small areas can be made easy from the control point of view by using hexagonal set-based instead of square NMPCs.application/pdf6 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Nonlinear MPCUnmanned VehiclesEnvironmental MissionsWater Quality Assessmentinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.ifacol.2022.11.017