Adaptive and Neuro Adaptive Control for Intensive Care Unit Sedation and Intraoperative Anesthesia

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Abstract Haddad The objective of this research is to develop active control algorithms to significantly advance our understanding of the wide effects of pharmacological agents and anesthetics, as well as advance the state-of-the-art in active control of drug delivery systems for clinical pharmacology. In the practice of critical care medicine it is current clinical practice to administer potent drugs that profoundly influence levels of consciousness, respiratory, and cardiovascular function by manual control based on the clinician's experience and intuition. This project will investigate the use of closed-loop control based on appropriate dynamical system models as an alternative means of improving drug delivery in the operating room and the intensive care unit. The PI will develop adaptive control algorithms using nonnegative and compartmental system theory for the specific problem of closed-loop control of drug dosing. Specifically, he will develop adaptive control and neural network adaptive control algorithms for intensive care unit sedation and itraoperative anesthesia. Intellectual merit. Although the theories of adaptive and neuro adaptive control have been extensively addressed for linear and nonlinear systems in the literature, a unified linear and nonlinear control design framework for nonnegative and compartmental dynamical systems remains relatively undeveloped. This is due to the fact that nonnegative and compartmental systems have highly specialized structures and control (source) inputs are usually constrained to be nonnegative as are the states of the compartments. Broader benefits. This research will amalgamate control theory and pharmacology to provide efficient solutions to the challenging problem of automated anesthesia. Promising control algorithms will be implemented for the delivery of intraoperative anesthesia and intensive care unit sedation on site at the Northeast Georgia Medical Center. Payoffs would arise from improvements in medical care, health care, reliability of drug dosing equipment, and reduced cost for health care.