Multi-criteria performance assessment based on closed-loop system identification

10.36227/techrxiv.16817551.v1 ◽

2021 ◽

Author(s):

Gustavo Sanchez

Keyword(s):

System Identification ◽

Closed Loop ◽

Process Variable ◽

Loop System ◽

Closed Loop Control ◽

Closed Loop System ◽

Trade Off ◽

Loop Control ◽

Control Loops ◽

Variable Energy

<div>A method to assess the performance of closed loop control loops, based on closed-loop system identification. This method allows to take into account the trade-off between process variable and manipulated variable energy, thus overcoming one of the most important criticisms to Harris' index. </div>

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Dual-hormone closed loop system using a liquid stable glucagon formulation versus insulin-only closed loop system compared to a predictive low glucose suspend system: an open label, outpatient, single center, crossover, randomized control trial

10.2337/figshare.12815861 ◽

2020 ◽

Cited By ~ 1

Author(s):

Leah M. Wilson ◽

Peter G. Jacobs ◽

Katrina L. Ramsey ◽

Navid Resalat ◽

Ravi Reddy ◽

...

Keyword(s):

Closed Loop ◽

Artificial Pancreas ◽

Loop System ◽

Target Range ◽

Closed Loop Control ◽

Closed Loop System ◽

Entire Study ◽

Loop Control ◽

Study Duration ◽

Low Glucose

Objective: To assess the efficacy and feasibility of a dual-hormone closed loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed loop system and a predictive low glucose suspend system. Research Design and Methods: In a 76-hour, randomized, crossover, outpatient study, 23 participants with type 1 diabetes used three modes of the Oregon Artificial Pancreas system: (1) dual-hormone (DH) closed loop control, (2) insulin-only single-hormone (SH) closed loop control and (3) predictive low glucose suspend (PLGS). The primary endpoint was percent time in hypoglycemia (<70 mg/dL) from start of in-clinic aerobic exercise (45mins at 60% VO2max) to 4 hours after. Results: DH reduced hypoglycemia compared with SH during and after exercise (DH 0.0% [0.0-4.2], SH 8.3% [0.0-12.5], p=0.025). There was an increased time in hyperglycemia (>180mg/dL) during and after exercise for DH vs SH (20.8% DH vs. 6.3% SH, p=0.038). Mean glucose during the entire study duration was: DH 159.2, SH 151.6, PLGS 163.6 mg/dL. Across the entire study duration, DH resulted in 7.5% more time in target range (70-180 mg/dL) compared with the PLGS system (71.0% vs. 63.4%, p=0.044). For the entire study duration, DH had 28.2% time in hyperglycemia versus 25.1% for SH (p=0.044) and 34.7% for PLGS (p=0.140). Four participants experienced nausea related to glucagon leading 3 to withdraw from the study. Conclusions: The glucagon formulation demonstrated feasibility in a closed loop system. The dual-hormone system reduced hypoglycemia during and after exercise with some increase in hyperglycemia.

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Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

Endocrine Reviews ◽

10.1210/er.2018-00174 ◽

2019 ◽

Vol 40 (6) ◽

pp. 1521-1546 ◽

Cited By ~ 9

Author(s):

Rayhan A Lal ◽

Laya Ekhlaspour ◽

Korey Hood ◽

Bruce Buckingham

Keyword(s):

Type 1 Diabetes ◽

Glucose Control ◽

Closed Loop ◽

Diabetes Management ◽

Artificial Pancreas ◽

Loop System ◽

Closed Loop Control ◽

Closed Loop System ◽

Loop Control

Abstract Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an “artificial pancreas” that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

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Dual-hormone closed loop system using a liquid stable glucagon formulation versus insulin-only closed loop system compared to a predictive low glucose suspend system: an open label, outpatient, single center, crossover, randomized control trial

10.2337/figshare.12815861.v1 ◽

2020 ◽

Author(s):

Leah M. Wilson ◽

Peter G. Jacobs ◽

Katrina L. Ramsey ◽

Navid Resalat ◽

Ravi Reddy ◽

...

Keyword(s):

Closed Loop ◽

Artificial Pancreas ◽

Loop System ◽

Target Range ◽

Closed Loop Control ◽

Closed Loop System ◽

Entire Study ◽

Loop Control ◽

Study Duration ◽

Low Glucose

Objective: To assess the efficacy and feasibility of a dual-hormone closed loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed loop system and a predictive low glucose suspend system. Research Design and Methods: In a 76-hour, randomized, crossover, outpatient study, 23 participants with type 1 diabetes used three modes of the Oregon Artificial Pancreas system: (1) dual-hormone (DH) closed loop control, (2) insulin-only single-hormone (SH) closed loop control and (3) predictive low glucose suspend (PLGS). The primary endpoint was percent time in hypoglycemia (<70 mg/dL) from start of in-clinic aerobic exercise (45mins at 60% VO2max) to 4 hours after. Results: DH reduced hypoglycemia compared with SH during and after exercise (DH 0.0% [0.0-4.2], SH 8.3% [0.0-12.5], p=0.025). There was an increased time in hyperglycemia (>180mg/dL) during and after exercise for DH vs SH (20.8% DH vs. 6.3% SH, p=0.038). Mean glucose during the entire study duration was: DH 159.2, SH 151.6, PLGS 163.6 mg/dL. Across the entire study duration, DH resulted in 7.5% more time in target range (70-180 mg/dL) compared with the PLGS system (71.0% vs. 63.4%, p=0.044). For the entire study duration, DH had 28.2% time in hyperglycemia versus 25.1% for SH (p=0.044) and 34.7% for PLGS (p=0.140). Four participants experienced nausea related to glucagon leading 3 to withdraw from the study. Conclusions: The glucagon formulation demonstrated feasibility in a closed loop system. The dual-hormone system reduced hypoglycemia during and after exercise with some increase in hyperglycemia.

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Day and Night Closed-Loop Control Using the Integrated Medtronic Hybrid Closed-Loop System in Type 1 Diabetes at Diabetes Camp

Diabetes Care ◽

10.2337/dc14-3073 ◽

2015 ◽

Vol 38 (7) ◽

pp. 1205-1211 ◽

Cited By ~ 85

Author(s):

Trang T. Ly ◽

Anirban Roy ◽

Benyamin Grosman ◽

John Shin ◽

Alex Campbell ◽

...

Keyword(s):

Type 1 Diabetes ◽

Closed Loop ◽

Loop System ◽

Closed Loop Control ◽

Closed Loop System ◽

Loop Control ◽

Diabetes Camp

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Multi-Stage System Identification of a Gas Turbine

Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy ◽

10.1115/gt2017-64777 ◽

2017 ◽

Author(s):

Amit Pandey ◽

Maurício de Oliveira ◽

Chad M. Holcomb

Keyword(s):

Gas Turbine ◽

Closed Loop ◽

Open Loop ◽

Loop System ◽

Closed Loop Control ◽

Input Output ◽

Open Loop System ◽

Loop Control ◽

Multi Stage ◽

Identification Techniques

Several techniques have recently been proposed to identify open-loop system models from input-output data obtained while the plant is operating under closed-loop control. So called multi-stage identification techniques are particularly useful in industrial applications where obtaining input-output information in the absence of closed-loop control is often difficult. These open-loop system models can then be employed in the design of more sophisticated closed-loop controllers. This paper introduces a methodology to identify linear open-loop models of gas turbine engines using a multi-stage identification procedure. The procedure utilizes closed-loop data to identify a closed-loop sensitivity function in the first stage and extracts the open-loop plant model in the second stage. The closed-loop data can be obtained by any sufficiently informative experiment from a plant in operation or simulation. We present simulation results here. This is the logical process to follow since using experimentation is often prohibitively expensive and unpractical. Both identification stages use standard open-loop identification techniques. We then propose a series of techniques to validate the accuracy of the identified models against first principles simulations in both the time and frequency domains. Finally, the potential to use these models for control design is discussed.

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