Human-in-the-loop model predictive control of an irrigation canal


Reference:
P.J. van Overloop, J.M. Maestre, A.D. Sadowska, E.F. Camacho, and B. De Schutter, "Human-in-the-loop model predictive control of an irrigation canal," IEEE Control Systems Magazine, vol. 35, no. 4, pp. 19-29, Aug. 2015.

Abstract:
This article contributes towards extending the scope of human-in-the-loop (HIL) control for systems when human operators serve as actuators or sensors. In particular, this work concerns those situations where humans are operators of the control system requiring their actions on a regular basis. That is, no human decision is involved in the control, although the control system relies on the operators to implement the control actions and to perform measurements. In this article, a large-scale system consisting of cascade-connected subsystems that influence each other through mutual interrelations is considered. Although there might be local automatic controllers within each subsystem, the actions of the human operators form the nucleus of the overall system operation. More specifically, it is assumed that there are a number of operators working within the system as sensors and actuators. However, the fact that the number of operators is less than the number of subsystems in the large-scale system directly implies that both the sensing and the actuating processes have a sparse nature, which diminishes the performance of the system with respect to standard fully-automatic methods. The key idea of the HIL approach presented in this article is to optimize the operators’ work in real time by integrating their labor into an online optimization problem that maximizes the performance of the system. In addition to operating in real time, it is also convenient to explicitly consider event-triggered approaches. The contributions of this article are twofold. Primarily, a novel HIL-MPC scheme for a large-scale system with multiple operators to serve as sensors and actuators is presented. Given the mobility of the operator, the new approach is thereafter referred to as Mobile MPC (MoMPC). Secondly, the MoMPC approach is tested on an accurate numerical model of an irrigation canal, namely the Dez canal in Iran. In this way, a realistic performance evaluation of MoMPC can be executed.


Downloads:
 * Online version of the paper

Bibtex entry:

@article{vanMae:15-004,
        author={P.J. van Overloop and J.M. Maestre and A.D. Sadowska and E.F. Camacho and B. {D}e Schutter},
        title={Human-in-the-loop model predictive control of an irrigation canal},
        journal={IEEE Control Systems Magazine},
        volume={35},
        number={4},
        pages={19--29},
        month=aug,
        year={2015},
        doi={10.1109/MCS.2015.2427040}
        }



Go to the publications overview page.


This page is maintained by Bart De Schutter. Last update: November 21, 2016.