Fault Detection in the Automatic Co-administration of Two Drugs for General Anesthesia

https://doi.org/10.58571/CNCA.AMCA.2025.007

Resumen: The administration of general anesthesia involves various inherent risks for patients, which has driven the development of automation aimed at ensuring precise drug delivery. Automation consists of regulating the Depth of Hypnosis (DoH), considering the infusion of drugs as control variables. This paper presents a fault detection strategy for an automated drug delivery system that regulates the DoH. The strategy considers the patient’s pharmacokinetic and pharmacodynamic linear models under the action of a model predictive control for DoH regulation. The approach employs the design of an interval observer that exploits the cooperativity property of the estimation error to enhance fault sensitivity and robustness against uncertainties. The proposed algorithm’s performance is evaluated through in silico simulations under different fault scenarios related to the blockage of the infusion pumps. The results demonstrate the effectiveness of the strategy in detecting faults in the actuators responsible for administering propofol and remifentanil.

¿Cómo citar?

Ramíırez–Barrios, M., Avilés, J. & Mera, M. (2025). Fault Detection in the Automatic Co-administration of Two Drugs for General Anesthesia. Memorias del Congreso Nacional de Control Automático 2025, pp. 38-43. https://doi.org/10.58571/CNCA.AMCA.2025.007

Palabras clave

Fault Detection, Interval Observers, Cooperative-Positive Systems, Anesthesia.

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