Mobile Robot Model Predictive Control Approach: Case Study of an Irrigation Canal

Abstract

We propose a stochastic model predictive control (SMPC) in combination with a mobile robot to address a control problem for an irrigation canal with uncertain dynamics. We impose tightened constraints over the sampling time of the prediction horizon to make the controller calculate the best route for the robot to gather new measurements for the MPC controller. This MPC strategy with a robot in the loop is validated using a numerical model of an ASCE Test Canal as a case study.