Map Meshing Impact on the Efficiency of Nonlinear Set-based Model Predictive Control for Water Quality Assessment

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.