A PI-fuzzy logic controller for the regulation of blood glucose level in diabetic patients.
This manuscript investigates different fuzzy logic controllers for the regulation of blood glucose level in diabetic patients. While fuzzy logic control is still intuitive and at a very early stage, it has already been implemented in many industrial plants and reported results are very promising. A fuzzy logic control (FLC) scheme was recently proposed for maintaining blood glucose level in diabetics within acceptable limits, and was shown to be more effective with better transient characteristics than conventional techniques. In fact, FLC is based on human expertise and on desired output characteristics, and hence does not require precise mathematical models. This observation makes fuzzy rule-based technique very suitable for biomedical systems where models are, in general, either very complicated or over-simplistic. Another attractive feature of fuzzy techniques is their insensitivity to system parameter variations, as numerical values of physiological parameters are often not precise and usually vary from patient to another. PI and PID controllers are very popular and are efficiently used in many industrial plants. Fuzzy PI and PID controllers behave in a similar fashion to those classical controllers with the obvious advantage that the controller parameters are time dependant on the range of the control variables and consequently, result in a better performance. In this manuscript, a fuzzy PI controller is designed using a simplified design scheme and then subjected to simulations of the two common diabetes disturbances--sudden glucose meal and system parameter variations. The performance of the proposed fuzzy PI controller is compared to that of the conventional PID and optimal techniques and is shown to be superior. Moreover, the proposed fuzzy PI controller is shown to be more effective than the previously proposed FLC, especially with respect to the overshoot and settling time.
Balqa' Applied University, Al Huson University College, Jordan. mohib@huson.edu.jo
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M
Ibbini
D000465:Algorithms; D001185:Artificial Intelligence; D001786:Blood Glucose / Q000378:metabolism*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000188:drug therapy*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D005246:Feedback; D017143:Fuzzy Logic; D006801:Humans; D007328:Insulin / Q000008:administration & dosage*; D008954:Models, Biological
D001786:Blood Glucose; D007328:Insulin