302 research outputs found

    Cautious NMPC with Gaussian Process Dynamics for Autonomous Miniature Race Cars

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    This paper presents an adaptive high performance control method for autonomous miniature race cars. Racing dynamics are notoriously hard to model from first principles, which is addressed by means of a cautious nonlinear model predictive control (NMPC) approach that learns to improve its dynamics model from data and safely increases racing performance. The approach makes use of a Gaussian Process (GP) and takes residual model uncertainty into account through a chance constrained formulation. We present a sparse GP approximation with dynamically adjusting inducing inputs, enabling a real-time implementable controller. The formulation is demonstrated in simulations, which show significant improvement with respect to both lap time and constraint satisfaction compared to an NMPC without model learning

    Cardiac and renal function in a large cohort of amateur marathon runners

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    Background Participation of amateur runners in endurance races continues to increase. Previous studies of marathon runners have raised concerns about exercise-induced myocardial and renal dysfunction and damage. In our pooled analysis, we aimed to characterize changes of cardiac and renal function after marathon running in a large cohort of mostly elderly amateur marathon runners. Methods A total of 167 participants of the BERLIN-MARATHON (female n = 89, male n = 78; age = 50.3 ± 11.4 years) were included and cardiac and renal function was analyzed prior to, immediately after and 2 weeks following the race by echocardiography and blood tests (including cardiac troponin T, NT- proBNP and cystatin C). Results Among the runners, 58% exhibited a significant increase in cardiac biomarkers after completion of the marathon. Overall, the changes in echocardiographic parameters for systolic or diastolic left and right ventricular function did not indicate relevant myocardial dysfunction. Notably, 30% of all participants showed >25% decrease in cystatin C-estimated glomerular filtration rate (GFR) from baseline directly after the marathon; in 8%, we observed a decline of more than 50%. All cardiac and renal parameters returned to baseline ranges within 2 weeks after the marathon. Conclusions The increase in cardiac biomarkers after completing a marathon was not accompanied by relevant cardiac dysfunction as assessed by echocardiography. After the race, a high proportion of runners experienced a decrease in cystatin C-estimated GFR, which is suggestive of transient, exercise-related alteration of renal function. However, we did not observe persistent detrimental effects on renal function

    Cardiovascular Remodeling Experienced by Real-World, Unsupervised, Young Novice Marathon Runners.

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    Aims: Marathon running is a popular ambition in modern societies inclusive of non-athletes. Previous studies have highlighted concerning transient myocardial dysfunction and biomarker release immediately after the race. Whether this method of increasing physical activity is beneficial or harmful remains a matter of debate. We examine in detail the real-world cardiovascular remodeling response following competition in a first marathon. Methods: Sixty-eight novice marathon runners (36 men and 32 women) aged 30 ± 3 years were investigated 6 months before and 2 weeks after the 2016 London Marathon race in a prospective observational study. Evaluation included electrocardiography, cardiopulmonary exercise testing, echocardiography, and cardiovascular magnetic resonance imaging. Results: After 17 weeks unsupervised marathon training, runners revealed a symmetrical, eccentric remodeling response with 3-5% increases in left and right ventricular cavity sizes, respectively. Blood pressure (BP) fell by 4/2 mmHg (P < 0.01) with reduction in arterial stiffness, despite only 11% demonstrating a clinically meaningful improvement in peak oxygen consumption with an overall non-significant 0.4 ml/min/kg increase in peak oxygen consumption (P = 0.14). Conclusion: In the absence of supervised training, exercise-induced cardiovascular remodeling in real-world novice marathon runners is more modest than previously described and occurs even without improvement in cardiorespiratory fitness. The responses are similar in men and women, who experience a beneficial BP reduction and no evidence of myocardial fibrosis or persistent edema, when achieving average finishing times

    Stochastic Model Predictive Control for Linear Systems using Probabilistic Reachable Sets

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    In this paper we propose a stochastic model predictive control (MPC) algorithm for linear discrete-time systems affected by possibly unbounded additive disturbances and subject to probabilistic constraints. Constraints are treated in analogy to robust MPC using a constraint tightening based on the concept of probabilistic reachable sets, which is shown to provide closed-loop fulfillment of chance constraints under a unimodality assumption on the disturbance distribution. A control scheme reverting to a backup solution from a previous time step in case of infeasibility is proposed, for which an asymptotic average performance bound is derived. Two examples illustrate the approach, highlighting closed-loop chance constraint satisfaction and the benefits of the proposed controller in the presence of unmodeled disturbances.Comment: 57th IEEE Conference on Decision and Control, 201

    Service Dominant Logic and Business Process Blueprinting: Enhancing the View on Performance by Integrating the Customer Perspective

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    Today process-oriented approaches to solve business challenges are state of the art. However most business process management methods focus on increased performance only from the firm’s perspective and neglect the increasing importance of value co-creation between the firm and the customer. Modern business process management methods not only need to concentrate on the internal performance of processes, but need to include the customer’s perspective. In this article we introduce the method of “Business Process Blueprinting” that combines both points of view. By enhancing business process modeling with the marketing concept of service blueprinting, we offer a method to visualize and analyze the firm’s and customer’s perspective within one integrated approach and reduce the gap between information management and marketing. This opens up the path towards an enhanced understanding of process performance in terms of a stronger inclusion of revenue into costing and analyzing and influencing subsequent usage processes

    A risk analysis framework for real-time control systems

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    We present a Monte Carlo simulation framework for analysing the risk involved in deploying real-time control systems in safety-critical applications, as well as an algorithm design technique allowing one (in certain situations) to robustify a control algorithm. Both approaches are very general and agnostic to the initial control algorithm. We present examples showing that these techniques can be used to analyse the reliability of implementations of non-linear model predictive control algorithms.Comment: v2: Major changes. Corrected several theoretical issues in v1 and recomputed example
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