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A major obstacle in the design of controllers to regulate the depth of anesthesia (DoA) consists in the high model uncertainty due to inter-patient variability. Surprisingly, the use of control design methods that explicitly tackle this problem is almost absent from the literature on automatic control of anesthesia. In this work, a DoA controller is designed taking into account model uncertainty to...
Due to their underlying complexity, biomedical systems are typically described by dynamic models with a significant level of uncertainty. Hence, classical control methods cannot be readily applied, as they do not render satisfactory results in terms of performance and even stability. Therefore, this paper proposes a multiple-model adaptive approach to the neuromuscular blockade control problem, based...
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