OBJECTIVE: The goal of this paper was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness. METHODS: We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce the interpatient variability and a new robust PID controller was designed using an optimization-based method. We evaluated this optimized design in a clinical study involving 16 new cases. RESULTS: The optimized controller design achieved the performance predicted in simulation studies in the design stage. Time of induction of anesthesia was median [Q1, Q3] 3.7 [2.3, 4.1] min and the achieved global score was 13.4 [9.9, 16.8]. CONCLUSION: Allometric scaling reduces the interpatient variability in this age group and allows for improved closed-loop performance. The uncertainty described by the model set, the predicted closed-loop responses, and the predicted robustness margins are realistic. The system meets the design objectives of improved speed of induction of anesthesia while maintaining robustness and improving clinically relevant system behavior. SIGNIFICANCE: Control system optimization and ongoing system improvements are essential to the development of a clinically relevant commercial device. This paper demonstrates the validity of our approach, including system modeling, controller optimization, and pre-clinical testing in simulation.
OBJECTIVE: The goal of this paper was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness. METHODS: We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce the interpatient variability and a new robust PID controller was designed using an optimization-based method. We evaluated this optimized design in a clinical study involving 16 new cases. RESULTS: The optimized controller design achieved the performance predicted in simulation studies in the design stage. Time of induction of anesthesia was median [Q1, Q3] 3.7 [2.3, 4.1] min and the achieved global score was 13.4 [9.9, 16.8]. CONCLUSION: Allometric scaling reduces the interpatient variability in this age group and allows for improved closed-loop performance. The uncertainty described by the model set, the predicted closed-loop responses, and the predicted robustness margins are realistic. The system meets the design objectives of improved speed of induction of anesthesia while maintaining robustness and improving clinically relevant system behavior. SIGNIFICANCE: Control system optimization and ongoing system improvements are essential to the development of a clinically relevant commercial device. This paper demonstrates the validity of our approach, including system modeling, controller optimization, and pre-clinical testing in simulation.
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