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State Space Model Predictive Control of an Aerothermic Process with Actuators Constraints

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Author(s): Mohamed Haloua | Hussein Youlal | Mustapha Ramzi

Journal: Journal of Biophysical Chemistry
ISSN 2153-036X

Volume: 03;
Issue: 01;
Start page: 50;
Date: 2012;
Original page

Keywords: Multi-Variable Control | Aerothermic Process | Actuators Constraints | Process Identification | State Space Model Predictive Control

ABSTRACT
This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.
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