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Accuracy of the HeartMate 3 Left Ventricular Assist Device Flow Estimation

Scientific reports 2025年第1期15卷 18971页

作者： Theodor Abart Marko Grujic Philipp Aigner Michael Röhrich Stefan Jakubek Daniel Zimpfer Marcus Granegger Christian Doppler Laboratory for Mechanical Circulatory Support Department of Cardiac and Thoracic Aortic Surgery Medical University of Vienna Vienna Austria. Department of Anesthesia Intensive Care Medicine and Pain Medicine Medical University of Vienna Vienna Austria. Division of Control and Process Automation Institute of Mechanics and Mechatronics Vienna University of Technology Vienna Austria. Christian Doppler Laboratory for Mechanical Circulatory Support Department of Cardiac and Thoracic Aortic Surgery Medical University of Vienna Vienna Austria. marcus.granegger@meduniwien.ac.at.

Left ventricular assist devices (LVADs), such as the HeartMate 3 (HM3), are a treatment option for advanced heart failure (HF). Non-invasive monitoring of heart-pump interaction is crucial but relies on estimated parameters only. Despite the widespread clinical utilization of HM3 estimated flow rate (Q) and pulsatility index (PI) their accuracy was not yet quantified. This study assessed the HM3 monitoring by describing underlying physical characteristics, estimation algorithms and deriving accuracy of estimates in clinical practice. Identification measurements were performed to quantify the physical characteristics and mechanisms of flow estimation. Virtual patients coupled to a hybrid hock circulatory loop were employed to evaluate estimator accuracies in realistic operating conditions. The correlation between Q and torque-generating-current was strong (r² > 0.99, p < 0.001), confirming that estimation is based on speed, current, and viscosity. Also, the PI is directly derived from current. However, the underlying current/flow relationship is ambiguous (one current value corresponds to two flow rates). The HM3 flow estimator showed an RMSE of 1.63 L/min and a correlation coefficient of r = 0.86 (p < 0.001). The non-linear relationship obscures the systolic portion of flow as current declines during peak systole at higher flow rates. HM3 monitoring is unable to accurately represent the actual hemodynamics, particularly in the transition between full support and partial support, which is a region highly prevalent and crucial in clinical practice. It is therefore recommended to interpret values and trends of the HM3 monitoring system with caution.

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

arXiv

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arXiv 2020年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Electrical Engineering University of North Texas DentonTX76203 United States The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal–dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We show that the proposed algorithm achieves the linear speedup convergence rate O(1/√nT) for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, where T is the total number of iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost functions

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A hierarchical MPC for multi-objective mixed-integer optimisation applied to redundant refrigeration circuits

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IFAC-PapersOnLine 2017年第1期50卷 9058-9064页

作者： Luchini E. Schirrer A. Kozek M. Institute of Mechanics and Mechatronics Division of Control and Process Automation Getreidemarkt 9/325-A5 Vienna A-1060 Austria

Temperature control of an insulated cool box (ICB) can be efficiently provided by model predictive control. However, if the cooling capacity is supplied by redundant refrigeration circuits (RCs) with both continuous and switched control variables, the overall control design becomes complex: 1) Time constants of the ICB and RCs differ by a factor of approximately 100. 2) Switched and continuous control variables require mixed-integer optimisation. 3) Power consumption, wear, control performance and output tracking call for multi-objective optimisation. In this work a global linear Model Predictive controller (MPC) is designed to compute a desired cooling capacity at a low sampling frequency for a long prediction horizon, while a mixed-integer MPC (MI-MPC) provides the actual cooling capacity utilising a fast sampling frequency and a short prediction horizon. The control concept is presented, a stability prove is given and simulation results demonstrate the performance of the concept. © 2017

关键词： hierarchical MPC mixed-integer optimisation multiple sampling rates refrigeration system

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Exponential convergence for distributed smooth optimization under the restricted secant inequality condition

arXiv

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arXiv 2019年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Chai, Tianyou Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the distributed smooth optimization problem in which the objective is to minimize a global cost function formed by a sum of local smooth cost functions, by using local information exchange. The standard assumption for proving exponential/linear convergence of first-order methods is the strong convexity of the cost functions, which does not hold for many practical applications. In this paper, we first show that the continuous-time distributed primal-dual gradient algorithm converges to one global minimizer exponentially under the assumption that the global cost function satisfies the restricted secant inequality condition. This condition is weaker than the strong convexity condition since it does not require convexity and the global minimizers are not necessary to be unique. We then show that the discrete-time distributed primal-dual algorithm constructed by using the Euler's approximation method converges to one global minimizer linearly under the same condition. The theoretical results are illustrated by numerical simulations. Copyright © 2019, The Authors. All rights reserved.

关键词： Continuous time systems

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Linear convergence of first- And zeroth-order primal-dual algorithms for distributed nonconvex optimization

arXiv

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arXiv 2019年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Digital Futures Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of local cost functions by using local information *** first propose a distributed first-order primal-dual algorithm. We show that it converges sublinearly to a stationary point if each local cost function is smooth and linearly to a global optimum under an additional condition that the global cost function satisfies the Polyak-Lojasiewicz condition. This condition is weaker than strong convexity, which is a standard condition for proving linear convergence of distributed optimization algorithms, and the global minimizer is not necessarily unique. Motivated by the situations where the gradients are unavailable, we then propose a distributed zeroth-order algorithm, derived from the proposed distributed first-order algorithm by using a deterministic gradient estimator, and show that it has the same convergence properties as the proposed first-order algorithm under the same conditions. The theoretical results are illustrated by numerical simulations. Copyright © 2019, The Authors. All rights reserved.

关键词： Cost functions

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Distributed bandit online convex optimization with time-varying coupled inequality constraints

arXiv

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arXiv 2019年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Johansson, Karl H. Chai, Tianyou Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the problem of distributed bandit online convex optimization with time-varying coupled inequality constraints. This problem can be defined as a repeated game between a group of learners and an adversary. The learners attempt to minimize a sequence of global loss functions and at the same time satisfy a sequence of coupled constraint functions. The global loss and the coupled constraint functions are the sum of local convex loss and constraint functions, respectively, which are adaptively generated by the adversary. The local loss and constraint functions are revealed in a bandit manner, i.e., only the values of loss and constraint functions at sampled points are revealed to the learners, and the revealed function values are held privately by each learner. We consider two scenarios, one- and two-point bandit feedback, and propose two corresponding distributed bandit online algorithms used by the learners. We show that sublinear expected regret and constraint violation are achieved by these two algorithms, if the accumulated variation of the comparator sequence also grows sublinearly. In particular, we show that O(T θ1 ) expected static regret and O(T 7/4−θ1 ) constraint violation are achieved in the one-point bandit feedback setting, and O(T max{κ,1−κ}) expected static regret and O(T 1−κ/2) constraint violation in the two-point bandit feedback setting, where θ1 ∈ (3/4, 5/6] and κ ∈ (0, 1) are user-defined trade-off parameters. Finally, these theoretical results are illustrated by numerical simulations of a simple power grid example. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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Realtime-capable FE-based railway catenary emulation via pantograph test rig impedance control

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IFAC-PapersOnLine 2017年第1期50卷 8636-8641页

作者： Aschauer G. Schirrer A. Kozek M. Jakubek S. Institute of Mechanics and Mechatronics Division of Control and Process Automation Technische Universität Wien Getreidemarkt 9/325-A5 Vienna A-1060 Austria

This work shows novel results of emulating railway catenary dynamics on a test rig for pantograph testing in order to provide for virtual test rides of railway pantograph current collectors under laboratory conditions. A realtime-capable finite-element model of a railway catenary is formulated efficiently in moving coordinates. An advanced test rig impedance control architecture is adopted for the finite-element model structure, and detailed simulations of an existing full-size pantograph test rig are carried out. The high fidelity of the realtime catenary model as well as the emulation performance of the closed-loop test rig setup in contact with a pantograph model provides promising results for the future implementation of the simulation/control architecture on the test rig hardware. © 2017

关键词： distributed-parameter systems finite elements Impedance control partial differential equations predictive control railways

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Finite time boundedness of switched delay systems by sliding mode technique 36

Finite time boundedness of switched delay systems by sliding...

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第36届中国控制会议

作者： Haijuan Zhao Yugang Niu Tinggang Jia Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division of Shanghai Electric Group Co. Ltd.

ISBN: (纸本)9781538629185

In this paper,the finite-time boundedness（FTB） problem of sliding mode control（SMC） is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is constructed to drive the state trajectories onto the integral sliding surface during a finite time *** FTB of the controlled systems on both reaching phase and siding motion phase are analyzed by means of average dwell time ***,a numerical example is given.

关键词： Switched delay system Finite time boundedness Sliding mode control Average dwell time

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Distributed Least Squares Solver for Network Linear Equations

arXiv

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arXiv 2018年

作者： Yang, Tao George, Jemin Qin, Jiahu Yi, Xinlei Wu, Junfeng State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China U.S. Army Research Laboratory AdelphiMD20783 United States Department of Automation University of Science and Technology of China Hefei230027 China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden College of Control Science and Engineering Zhejiang University Hangzhou310027 China

In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and holds a dynamic state. We first propose a distributed least square solver over connected undirected interaction graphs and establish a necessary and sufficient on the step-size under which the algorithm exponentially converges to the least square solution. Next, we develop a distributed least square solver over strongly connected directed graphs and show that the proposed algorithm exponentially converges to the least square solution provided the step-size is sufficiently small. Moreover, we develop a finite-time least square solver by equipping the proposed algorithms with a finite-time decentralized computation mechanism. The theoretical findings are validated and illustrated by numerical simulation examples. Copyright © 2018, The Authors. All rights reserved.

关键词： Linear equations

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Real-time capable nonlinear pantograph models using local model networks in state-space configuration

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IFAC-PapersOnLine 2016年第21期49卷 157-162页

作者： Maier, Clemens C. Schirrer, Alexander Kozek, Martin Technische Universität Wien Institute of Mechanics and Mechatronics Division of Control and Process Automation ViennaA-1060 Austria

Modern pantograph current collectors for high-speed trains are mechatronic systems that are increasingly equipped with active control to maximize their dynamic performance. To realize a high-quality contact, decrease wear, and increase speed, it is necessary to use high-fidelity co-simulation and hardware-in-the-loop (HiL) testing tools, as well as modern model-based control (MBC) concepts. In all these areas, efficient, real-time-capable and accurate models of the pantograph dynamics are required. This paper proposes two different real-time-capable nonlinear pantograph models based on the local model network (LMN) methodology, intended for utilization in co-simulation and control design. They are identifiable by measurement data and applicable for different pantograph geometries. The proposed model structures attain significant improvements in accuracy compared to classical models via global linearization, and they are highly computationally efficient. © 2016

关键词： Electric current collection Fuzzy neural networks MIMO systems Model structures Pantographs Quality control Railroad cars Railroads Computationally efficient Hardware in the loops High speed train (HST) Model based controls Neuro fuzzy network Non linear model Real time capability Subspace identification

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