Robust Model Predictive Control of Heat Exchangers

Abstract

The paper attempts to show that using the robust model-based predictive control (RMPC) strategy for control of thermal processes can lead to energy savings in comparison with classical control approaches. RMPC is applied for control of a tubular heat exchanger that is used for pre-heating petroleum by hot water. The heat exchanger is a nonlinear system with time delay and uncertainty. The control objective is to keep the output temperature of the heated stream at a reference value and minimize the energy consumption needed for petroleum heating. The advantage of RMPC is that it is the optimisation based strategy, the control input and controlled outputs constraints are directly included into the synthesis and uncertainty of the process model is taken into account. RMPC of the heat exchanger is compared with the classical optimal linear quadratic (LQ) control by simulations experiments. In the presence of uncertainty and boundaries on control inputs, using the RMPC approach increases the quality of the control performance and decreases energy supplied to the heating medium.