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


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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M. Ramzi, H. Youlal and M. Haloua, "State Space Model Predictive Control of an Aerothermic Process with Actuators Constraints," Intelligent Control and Automation, Vol. 3 No. 1, 2012, pp. 50-58. doi: 10.4236/ica.2012.31007.

Conflicts of Interest

The authors declare no conflicts of interest.


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