53rd IEEE Conference on Decision and Control. 15-17 Dec. 2014 Los Angeles, CA, USAIn this work, we propose to expand the application of model predictive control (MPC) to problems in which there are human agents involved in the sensing and actuation processes. To this end, a new configuration of a control system structure that combines centralized predictive control and local operations is presented. Additional constraints are included in the optimization problem to take into account the mobility and the role of the operators over the prediction horizon. This new type of control system structure, referred to as Mobile Model Predictive Control (MoMPC), is tested on a linear model of a large scale irrigation canal and its performance is compa...
A system generally has one or more input signals and one or more output signals. By far, the greates...
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
This work addresses the problem of tuning the parameters of a distributed model predictive control a...
Mobile Model Predictive control is a novel control technique for irrigation canals that optimizes th...
Irrigation canals are large-scale systems, covering vast geographical areas, and consisting of many ...
In this master thesis, the recently introduced Mobile Model Predictive Control (MoMPC) approach for ...
Optimization techniques have played a fundamental role in designing automatic control systems for th...
Water networks are large-scale systems, consisting of many interacting components. They are currentl...
Until now, advanced model-based control techniques have been predominantly employed to control probl...
The performance achieved with both adaptive and non-adaptative Model Predictive Control (MPC) when a...
Abstract—Water networks are large-scale systems, consisting of many interacting components. They are...
International audienceThis paper presents the application of the multiagent paradigm to a distribute...
Irrigation canals transport water from water sources (such as large rivers and lakes) to water users...
This paper presents the formulation of a multivariable controller for centralized control of canals ...
Model predictive control (MPC) has been used successfully in industry. The basic characteristic of t...
A system generally has one or more input signals and one or more output signals. By far, the greates...
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
This work addresses the problem of tuning the parameters of a distributed model predictive control a...
Mobile Model Predictive control is a novel control technique for irrigation canals that optimizes th...
Irrigation canals are large-scale systems, covering vast geographical areas, and consisting of many ...
In this master thesis, the recently introduced Mobile Model Predictive Control (MoMPC) approach for ...
Optimization techniques have played a fundamental role in designing automatic control systems for th...
Water networks are large-scale systems, consisting of many interacting components. They are currentl...
Until now, advanced model-based control techniques have been predominantly employed to control probl...
The performance achieved with both adaptive and non-adaptative Model Predictive Control (MPC) when a...
Abstract—Water networks are large-scale systems, consisting of many interacting components. They are...
International audienceThis paper presents the application of the multiagent paradigm to a distribute...
Irrigation canals transport water from water sources (such as large rivers and lakes) to water users...
This paper presents the formulation of a multivariable controller for centralized control of canals ...
Model predictive control (MPC) has been used successfully in industry. The basic characteristic of t...
A system generally has one or more input signals and one or more output signals. By far, the greates...
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
This work addresses the problem of tuning the parameters of a distributed model predictive control a...