Experimental investigation of alternative robust model predictive control of a heat exchanger

Abstract Advanced control of heat exchangers is an important task for control engineers, as these devices belong to the key equipment in chemical, petrochemical, food and pharmaceutical industries, and they are energy-intensive processes. This study presents novel robust model-based predictive control (MPC) of a heat exchanger. Influence of uncertain parameters was taken into account to design robust model-based predictive controller. Resulting optimization problem with constraints was formulated in the form of linear matrix inequalities, and the convex optimization problem was solved using semi-definite programming. The proposed alternative robust MPC design method was implemented using the novel software MUP. Extensive case study of heat exchanger control was done to demonstrate effectiveness of the alternative robust MPC. This novel strategy was compared with known robust MPC approaches. Experimental results confirmed that the alternative robust MPC improved control performance and ensured energy savings during the heat exchanger operation.

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