Adaptive soft computing methods for control of hemodialysis machines

Abstract

Abstract-In hemodialysis systems the control of peristaltic pumps can be vital as these machines support and maintain life functions. In this paper different soft computing approaches are compared for the strict control of peristaltic pumps. An adaptive fuzzy logic and an adaptive neuro-fuzzy inference system are examined then compared with a classical PID controller. A fast controller is sought, which is insensitive in speak of disturbances and has no residual error. Finally, experiences of the designed controller on a real system are detailed in the paper.

LMI-Based Feedback Regulator Design via TP Transformation for Fluid Volume Control in Blood Purification Therapies

“…The structure of the model is based on the original one [9], whit the modification introduced in [11]. Here, the model comprises two branches, both with the same plant.…”

“…Furthermore, this technique has an important advantage compared to the existing methods [10,11]. Namely, the safety critical equipment (such as hemodialysis machines) is tested to verify and validate its behavior.…”

“…two decades), while it is capable tolerating the changes of the tube segment. The designed controller compared to the previous work results [9,10,11]. …”

“…Furthermore, a fuzzy system and an adaptive neurofuzzy network were designed and compared [9,10,11]. The goal of current work is to create a robust controller that is fast and lightweight and works over a wide flow range (approx.…”

Physiological modeling and control at Obuda University

“…These control methods were compared with a newly designed adaptive neuro-fuzzy inference system (ANFIS) [24]. The controllers were compared by settling time, overshoot and accuracy.…”