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Abstract

This paper describes the possibility of using Computational Fluid Dynamics (CFD) models for developing Model Predictive Controller (MPC) algorithms. In this work a complex CFD model is combined with a reduced order Data-Based Mechanistic (DBM) formulation so that the low-order model can be used for control applications. To demonstrate the methodology, a Single Input-Single Output (SISO) ventilated installation is used. Initially, a CFD model is used for the installation. At the inlet a step rise in air temperature is applied and temperature responses at 36 monitoring positions are extracted. Then a reduced order model is formulated for the test case and model parameters are identified using the data generated by the CFD model. Finally the reduced order CFD model is used to develop an MPC algorithm. The developed algorithm is found to be robust for disturbance effects and capable of tracking the desired reference temperature trajectory very well.

Keywords

Computational Fluid Dynamics Model Disturbance Robust Temperature Model Predictive Controller

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Numerical Simulation and Controller Development for Energy Transfer in Imperfectly Mixed Fluids

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