Yu, T; Dua, V; (2019) Nonlinear Model Predictive Control of Haemodialysis. In: Kiss, AA and Zondervan, E and Lakerveld, R and Ozkan, L, (eds.) Computer Aided Chemical Engineering. (pp. pp. 1285-1290). Elsevier

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Abstract

Haemodialysis is a blood treatment technique used for patients whose kidneys are not working normally. A number of Linear Model Predictive Control (LMPC) formulations for controlling haemodialysis have been proposed in the literature. In this paper, a Nonlinear Model Predictive Control (NMPC) formulation is proposed that instead of using an approximated linear model takes into account the nonlinear model for haemodialysis. One of the key advantages of the NMPC formulation is that it gives more comprehensive control of the haemodialysis process. Four manipulated variables are considered: the blood flow out of the body, the blood flow returned from the dialysis machine to the body, the dialysate rate and the sodium concentration of the inlet blood flow. By manipulating these variables, the fluid volumes and the toxin clearance are monitored and controlled. The results show that a better control performance for the blood volumes and toxin clearance is obtained while the blood and dialysate flow rates are held at a relatively low level, which is expected to reduce the risk of adverse reactions for the patients.

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