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.
Publisher page
Downloads
BibTeX
@article{vanMae:15-004,
author = {van Overloop, Peter Jules and Maestre, Jos{\'{e}} M. and
Sadowska, Anna D. and Camacho, Eduardo F. and De Schutter, Bart},
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}
}