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作者： Reiterer, Florian Freckmann, Guido Re, Luigi del Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH University of Ulm Germany

Patients with type 1 diabetes mellitus (T1DM) typically determine their bolus insulin needs based on methods from Advanced Carbohydrate Counting (ACC). In ACC the amount of required bolus insulin is assumed to be directly proportional to the carbohydrate content of the ingested meal. It is well known that many T1DM patients have difficulties to accurately estimate meal carbohydrates. Though these estimates are used for calculating the meal bolus amount, there is a scarcity of data on how estimation errors affect glycemic control. The current paper analyzes the effect of carb counting errors on glycemic outcomes during basal-bolus-therapy in a simulation study using so-called Deviation Analyses. Furthermore, the effect of inaccurate estimates on the settings of the insulin therapy is studied by means of the previously published Adaptive Bolus Calculator (ABC) algorithm. It is found that whereas random carb counting inaccuracies indeed do lead to an inferior glycemic control, systematic biases in the estimates are expected to hardly affect the results since these are usually implicitly accounted for in the therapy settings. © 2018

关键词： Errors

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Identification of Mixed-Meal Effects on Insulin Needs and Glycemic control

Identification of Mixed-Meal Effects on Insulin Needs and Gl...

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作者： Reiterer, Florian Freckmann, Guido del Re, Luigi Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH University of Ulm Germany

Patients with type 1 diabetes mellitus (T1DM) usually determine their bolus insulin requirements using methods from advanced carbohydrate counting (ACC). In standard ACC only the carbohydrate content of the meal is used, whereas newer research suggests that also fat and protein should be considered. Especially meals with a high fat content are reported to require additional insulin. However, it remains disputed how to account for mixed meal composition appropriately when calculating bolus insulin needs. The current paper shows how the previously published Adaptive Bolus Calculator (ABC) method can be used to identify the effect of the mixed meal composition on the bolus insulin requirements. Additionally, a pragmatic strategy is proposed how the mixed meal composition can be taken into account when determining the bolus insulin needs with the ABC method. It is shown in Deviation Analysis simulations that taking into account the mixed meal composition for calculating the bolus insulin needs leads to a small, but statistically significant improvement in glycemic control. © 2019

关键词： Insulin

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Dynamic Full Range Input Shaping of Injection Parameters for Reduction of Transient NOx Emissions

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IFAC-PapersOnLine 2017年第1期50卷 3726-3731页

作者： Großbichler M. Schmied R. Waschl H. Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria

For modern passenger car Diesel engines strong limitations on emissions, due to legislation, require large efforts in combustion and aftertreatment control. This control problem is mainly approached by an intensive stationary calibration process and dynamic compensation techniques. However, large differences in combustion conditions between steady state, as used for calibration, and real transient maneuvers, such as tip-ins, can lead to undesired emission peaks. Against this background, the present work adapts a previously introduced input shaping strategy for injection parameters, such that it is applicable in the full engine operation range. Different to the former approach, the shape of the correction profile is determined directly from identified local models of the selected injection parameters to the NOx response. By using local linear models it is possible to consider variations in the system dynamics and parameterize the input shapers in an automated fashion. Additionally this approach can be applied together with a state of the art engine control, since it does not need a change in the base calibration. The improved strategy is evaluated on a passenger car Diesel engine and it is shown that a reduction of the undesired NOx overshoot can be achieved without impacting other performance indicators. © 2017

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Reduced Complexity Safety Testing for ADAS & ADF

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IFAC-PapersOnLine 2017年第1期50卷 5985-5990页

作者： Zhou J. Re L.D. Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Linz 4040 Austria

This paper focuses on systematical evaluation of Advanced Driver Assistance systems and Automated Driving Functions. To overcome the curse of dimensionality we propose to use a test case catalogue, which is proven to have a good coverage of critical traffic situation. Secondly, a method for assessment of safety performance is introduced. It is based on evaluating the performance limit of automated vehicle in a given test case and relating it to its overall exposure rate in real world traffic situations. Through a case study, the parametrization and generation of test scenarios and evaluation for an ADAS(ACC) system is presented. © 2017

关键词： Autonomous Vehicles Intelligent Driver Aids Safety Simulation

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Efficient mixed integer programming for autonomous overtaking

Efficient mixed integer programming for autonomous overtakin...

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2017 American control Conference, ACC 2017

作者： Molinari, Fabio Anh, Nguyen Ngoc Del Re, Luigi Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria

ISBN: (纸本)9781509059928

This paper addresses the autonomous overtaking problem using model predictive control. Accordingly, a mixed integer programming approach is put forward in which the surrounding vehicles are considered as moving obstacles. Unlike existing solutions using mixed integer programming, this paper presents more efficient formulations by reducing the number of binary variables, possibly enabling to accelerate the online computation. These algorithms are illustrated via a numerical example in the accurate vehicle simulator IPG CarMaker. © 2017 American Automatic control Council (AACC).

关键词： Model predictive control

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Feasibility of Fully Closed Loop Insulin Delivery in Type 2 Diabetes

Feasibility of Fully Closed Loop Insulin Delivery in Type 2 ...

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control Technology and Applications (CCTA),

作者： C. Ornetzeder F. Reiterer M. B. Christensen K. Nørgaard G. Freckmann L. del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Linz Austria Hvidovre University Hospital Hvidovre Denmark Steno Diabetes Center Copenhagen Gentofte Denmark Institut für Diabetes-Technologie Forschungs-und Entwicklungsgesellschaft mbH an der Universität Ulm Ulm Germany

Because of continuous technical progress over the last decades artificial pancreas (AP) systems have recently become reality for patients with type 1 diabetes (T1D) with first AP devices entering the market. However, all AP systems commercially under development are so-called hybrid closed loop systems, meaning that only the basal insulin is adjusted by the algorithm, whereas the meal boluses still have to be triggered manually by the patient. Fully closed loop systems for T1D that also administer meal boluses autonomously are so far mainly of academic interest. The biggest drawback of fully closed loop systems is that they can only give an insulin bolus as soon as a meal is detected from the recorded data, leading to significant delays in insulin delivery (and therefore more pronounced peaks in postprandial glucose) and/or an increased risk of hypoglycemia (in case of false positive detections). Contrary to almost all publications on the topic, the current paper investigates the feasibility of fully closed loop systems for patients with type 2 diabetes (T2D). Since glycemic variability tends to be significantly lower in T2D and since glucose dynamics are somewhat slower, fully closed loop systems seem in fact more favorable for this patient group than for T1D. The paper investigates the performance of available meal detection algorithms from the literature (developed for T1D patients) and modifies them for application in T2D. Additionally, the paper proposes a simple fully closed loop algorithm for T2D patients including a module for automatic meal bolusing and demonstrates its feasibility and safety.

关键词： Insulin Closed loop systems Sugar Diabetes Hospitals Fuzzy logic Pancreas

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Stochastic control based on convex lifting

Stochastic control based on convex lifting

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2017 American control Conference, ACC 2017

作者： Nguyen, Ngoc Anh Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Linz Austria

ISBN: (纸本)9781509059928

This paper presents a new method for stochastic control of linear systems affected by bounded additive disturbances while guaranteeing probabilistic constraints. This method relies on a so-called convex lifting, which will be proven to guarantee the recursive feasibility and closed-loop stability by means of the convergence to a stochastic positively invariant set. Moreover, this design procedure only requires to solve a linear programming problem at each instant, therefore, the online computation is cheap. Finally, a numerical example will be considered to illustrate the method. © 2017 American Automatic control Council (AACC).

关键词： Linear systems

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Reduced Complexity Safety Testing for ADAS & ADF

Reduced Complexity Safety Testing for ADAS & ADF

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作者： Zhou, Jinwei Re, Luigi del Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Linz4040 Austria

关键词： Safety testing

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Hybrid In Silico Evaluation Approach for Assessing Insulin Dosing Strategies

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IFAC-PapersOnLine 2017年第1期50卷 2051-2057页

作者： Reiterer F. Reiter M. del Re L. Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz url: http://desreg.jku.at Linz 4040 Austria

Instead of testing newly proposed insulin dosing algorithms directly in clinical trials, it is nowadays a common approach to first perform simulation studies using complex physiological models of the human glucose metabolism (so-called in silico evaluations). The most prominent example for this type of models is the FDA approved UVA/Padova simulator. As an alternative, several authors have developed methods in recent years that try to extrapolate the effect of a modified insulin therapy using real measurement data together with simple, linear models of insulin action. These methods will be referred to in the following as “Deviation Analysis” approaches. Even though Deviation Analyses and in silico evaluations with physiological models seem to be very different approaches at first glance, it is shown in this paper that this is not necessarily true. Deviation Analyses are not restricted to using linear time-invariant models for describing insulin action. On the contrary, it is even expected that physiologically more accurate models of insulin action increase the reliability of Deviation Analysis results. It is demonstrated in this paper how even a very complex model like the UVA/Padova simulator can be used as a tool for performing Deviation Analyses. The corresponding methodology represents a step towards bridging the gap between classical in silico evaluations and Deviation Analyses. © 2017

关键词： artificial pancreas biomedical system simulation Diabetes physiological model

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Nonlinear approach to virtual trials for insulin dosing systems

Nonlinear approach to virtual trials for insulin dosing syst...

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American control Conference

作者： Florian Reiterer Matthias Reiter Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz

ISBN: (纸本)9781509045839

Patients with type 1 diabetes mellitus (T1DM) need to supply their body with insulin from external sources in order to manage their blood glucose (BG) concentration and mitigate the long-term effects of a chronically increased BG level. Doing so is challenging and a heavy burden for those patients, which led to efforts of automating (parts of) this task. The trend to automated choice of insulin dosage, e.g. in Artificial pancreas (AP) systems, opens many new possibilities, but also challenges in terms of validation, as the number of freely tunable parameters (e.g. settings in an AP) can be so large that no clinical trial can assess the efficiency of all possible choices. As a consequence, computer model based trials - so called in silico evaluations - are getting increasingly popular. In recent times, several authors have tried to improve the quality of in silico evaluations by using "Deviation Analyses", a term used to refer to methods that extrapolate the effect of a modified insulin therapy using real measurement data together with simple, linear models of insulin action. However, due to the inherent linear model assumption in all methods proposed so far, large deviations compared to the insulin dosing scheme of the recorded data can lead to unphysiological results, e.g. to negative values in the computed glucose traces. Against this background a new, nonlinear methodology is proposed which effectively avoids the common pitfalls of linear Deviation Analyses approaches, i.e. the constant mode of insulin action.

关键词： Insulin Insulins linear models AP measurement data Dosing Type 1 Diabetes Mellitus basic group Clinical Trial Long-term effects Automation experimentation

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