abstract

• With recent advances in continuous glucose sensors and portable insulin pumps, the concept of an artificial pancreas is now feasible. However, due to continuous operation, the actuator in this system could fail in some degree. In this sense, this paper addresses model-based fault diagnosis using a glucose-insulin model developed by Hovorka et al. (2004), and extended with an interstitial compartment to reproduce subcutaneous glucose measurements. First, a nominal feedback controller is designed following a pole-placement technique and internal model principle. In addition, a feedforward action is included to compensate fast glucose excursions due to meals. For fault diagnosis purposes, meals are considered as partially known perturbations in the system, so their information is appended into the glucose-insulin model as an exosystem with nominal initial conditions. A nonlinear PI observer is then designed using the extended glucose-insulin model to generate a dedicated residual for fault diagnosis. After fault detection and identification, the controller gain is modified in order to compensate the effect of the fault. These ideas are validated in simulation under a closedloop configuration, and fault conditions of sub and over-dosing in the insulin pump.

authors

• Campos Delgado Daniel Ulises
• Espinoza Trejo Diego Rivelino
• Vega-Hernández O.

publication date

• 2009-01-01

published in

• 2009 6th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2009  Proceedings

keywords

• Artificial pancreas; Fault accommodation; Fault diagnosis; Health care systems safety Actuator fault; Closed-loop; Continuous operation; Controller gain; Exosystems; Fault accommodation; Fault conditions; Fault detection and identification; Fault diagnosis; Feed-Forward; Glucose measurements; Health-care system; Initial conditions; Insulin pumps; Internal model principle; Model-based fault diagnosis; Nominal feedback controller; PI observer; Pole placement technique; Actuators; Automation; Control; Controllers; Electrical engineering; Failure analysis; Fault tolerant computer systems; Glucose; Glucose sensors; Health care; Insulin; Process control; Pumps; Safety engineering; Fault detection

Digital Object Identifier (DOI)

• 10.1109/ICEEE.2009.5393405

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