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Automation in anesthesia : a look at L₁ adaptive and PID controllers Talebian, Kousha
Abstract
Control of anesthesia is one of the many tasks performed by anesthesiologists during surgery. It involves adjusting drug dosage by monitoring patient’s vital and clinical signs. A control system can replace this tedious and routine task, and allow the anesthesiologists to concentrate on more life threatening procedures. Because of large intra- and inter-variability in patients Pharmacokinetics and Pharmacodynamics responses, an adaptive controller is desirable. This thesis thoroughly investigates the L₁ Adaptive Control by applying it on 44 simulation cases which cover a wide range of patient demographics. It is found that the controller approaches an implantable non-adaptive LTI controller as the adaptation gain increases, echoing the results found by other researches. This loss of adaptivity is shown through examples and mathematical derivations. It is concluded that the L₁ Adaptive Control in its current form is not applicable to closed-loop control of anesthesia. As an alternative to adaptive controller, partial adaptivity in a PID controller is investigated. iControl, a PID controller designed by us, can sometimes lead to oscillation in the control signal. It is desirable to automatically detect the oscillations and tune the controller in order to remove them. A real-time oscillation detection algorithm is discussed. It detects multiple oscillations in real-time and provides their frequency, amplitude, severity and regularity. A PID auto-tuning algorithm is developed that uses the dominant frequency metrics provided by the oscillation detection algorithm to retune the controller robustly and to guarantee stability. This technique is simulated and tested on 44 cases; the gain and the phase margin in all 44 cases are within < 7% of the optimal tuning parameters of iControl.
Item Metadata
Title |
Automation in anesthesia : a look at L₁ adaptive and PID controllers
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2016
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Description |
Control of anesthesia is one of the many tasks performed by anesthesiologists during surgery. It involves adjusting drug dosage by monitoring patient’s vital and clinical signs. A control system can replace this tedious and routine task, and allow the anesthesiologists to concentrate on more life threatening procedures. Because of large intra- and inter-variability in patients Pharmacokinetics and Pharmacodynamics responses, an adaptive controller is desirable. This thesis thoroughly investigates the L₁ Adaptive Control by applying it on 44 simulation cases which cover a wide range of patient demographics. It is found that the controller approaches an implantable non-adaptive LTI controller as the adaptation gain increases, echoing the results found by other researches. This loss of adaptivity is shown through examples and mathematical derivations. It is concluded that the L₁ Adaptive Control in its current form is not applicable to closed-loop control of anesthesia. As an alternative to adaptive controller, partial adaptivity in a PID controller is investigated. iControl, a PID controller designed by us, can sometimes lead to oscillation in the control signal. It is desirable to automatically detect the oscillations and tune the controller in order to remove them. A real-time oscillation detection algorithm is discussed. It detects multiple oscillations in real-time and provides their frequency, amplitude, severity and regularity. A PID auto-tuning algorithm is developed that uses the dominant frequency metrics provided by the oscillation detection algorithm to retune the controller robustly and to guarantee stability. This technique is simulated and tested on 44 cases; the gain and the phase margin in all 44 cases are within < 7% of the optimal tuning parameters of iControl.
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Genre | |
Type | |
Language |
eng
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Date Available |
2017-01-21
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0340639
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2017-02
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International