TITLE:
State Space Model Predictive Control of an Aerothermic Process with Actuators Constraints
AUTHORS:
Mustapha Ramzi, Hussein Youlal, Mohamed Haloua
KEYWORDS:
Multi-Variable Control; Aerothermic Process; Actuators Constraints; Process Identification; State Space Model Predictive Control
JOURNAL NAME:
Intelligent Control and Automation,
Vol.3 No.1,
February
28,
2012
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.