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SICE International Symposium on control Systems (ISCS)

作者： Elisabeth Luchini Agnes Poks Dominik Radler Martin Kozek Division of Control and Process Automation Institute of Mechanics and Mechatronics Getreidemarkt 9/325-A5 Vienna Austria PRODUCTBLOKS GmbH Stockerauer Str. 106 Korneuburg Austria

ISBN: (数字)9784907764647

Temperature control of a food supplier vehicle with an insulated cool box (ICB) is critical. Air exchange during the door-opening is a main disturbance which heats up the ICB and accounts for a large part of total cooling load. Usually, this effect is not considered in the control strategy. In this paper a model predictive control (MPC) is used to optimise the temperature control and energy consumption and to handle the door-opening effects. Due to the thermal inertia of the cargo, it can be shown that a technique for estimating the temperature of the cargo instead of the air temperature would lead to a more effective control system. The system and control architecture is presented, the concept of the MPC including door-opening is given and simulation results demonstrate the performance of the concept.

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Wholistic simulation of an all-electric refrigerated delivery vehicle

Wholistic simulation of an all-electric refrigerated deliver...

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SICE International Symposium on control Systems (ISCS)

作者： Agnes Poks Elisabeth Luchini Filip Kitanoski Martin Kozek Division of Control and Process Automation Getreidemarkt 9/325-A5 Institute of Mechanics and Mechatronics Vienna Austria PRODUCTBLOKS GmbH Stockerauer Str. 106 Korneuburg Austria

ISBN: (数字)9784907764647

Large amounts of goods have to be discarded because of a disrupted cooling chain, where last mile delivery is often the crucial part. For future refrigerated trucks which are fully electrified the limited battery capacity calls for detailed investigations. The main contribution of this paper is a detailed model of such an electric truck together with an electric cooling unit, which covers both the power consumption of the drive train and the cooling unit for various driving conditions. The proposed simulation framework is parameterized using measured data from literature, it comprises different weather conditions, door openings, traffic volume as well as the driver aggressiveness. The simulation model uses a minimum number of parameters for an easy fit, and due to it computational efficiency it can be used for applications like model predictive control.

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Determination the installation efficiency of the evaporative air cooling in the greenhouse by temperature-moisture regime 1

Determination the installation efficiency of the evaporative...

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1st International Conference on Energetics, Civil and Agricultural Engineering, ICECAE 2020

作者： Anarbaev, A. Tursunov, O. Zakhidov, R. Kodirov, D. Vakhidov, U. Bozorov, E. Tuhtaeva, G. Babaev, A. Department of Power Supply and Renewable Energy Sources Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Tashkent100000 Uzbekistan School of Mechanical and Power Engineering Shanghai Jiao Tong University Shanghai200240 China Research Institute of Forestry Tashkent111104 Uzbekistan Department of Automation and Control of Technology Process Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Tashkent100000 Uzbekistan Department of Hydrology and Ecology Bukhara Branch of Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Bukhara Uzbekistan

The results of theoretical studies and experiments of the developed exhaust ventilation system with direct evaporative air-cooling with using "wet mats"are given. It has shown sufficient efficiency with increasing quality of flower cutting in the summer months. The effect of moisture on the operation of this system was studied. It is established that the heat absorption capacity of air directly depends on its temperature and relative humidity. It is also determined that the temperature of leaves and flowers in summer is usually 2 ÷ 7 °C greater than the air temperature in the greenhouses. In an experimental greenhouse, according to the results of experiments, the effectiveness of the developed installation for evaporative cooling of its operation was determined. © Published under licence by IOP Publishing Ltd.

关键词： Greenhouses

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Bipartite Consensus Problem of Harmonic Oscillators Based on Sampled-data

Bipartite Consensus Problem of Harmonic Oscillators Based on...

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第32届中国控制与决策会议

作者： Hang Tian Cheng-Lin Liu Guang-Ye Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University Shanghai Keliang Information Tech.& Eng.Co. Ltd

This paper is concerned with the bipartite consensus problem of sampled-data coupled harmonic oscillators by predictor factor under the fixed *** with the existing distributed protocol for synchronization in networks of coupled harmonic oscillators based on the sampled-data measurement,we propose a distributed bipartite consensus control protocol in which positive and negative interaction weights *** structurally balanced networks,we improve the convergence rate of the network via predictor *** and sufficient conditions are obtained for the well designed protocol to achieve bipartite consensus by using frequency-domain analysis and matrix ***,examples are shown to validate the convergence conditions.

关键词： Bipartite consensus Sampled-data coupled harmonic oscillators Predictor factor

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Accuracy of the HeartMate 3 Left Ventricular Assist Device Flow Estimation

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Scientific Reports 2025年第1期15卷 1-11页

作者： Abart, Theodor Grujic, Marko Aigner, Philipp Röhrich, Michael Jakubek, Stefan Zimpfer, Daniel Granegger, Marcus 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

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_est) 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_est 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. © The Author(s) 2025.

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Zeroth-order algorithms for stochastic distributed nonconvex optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 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

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

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Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

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Yarn-dyed Fabric Defect Detection using U-shaped De-noising Convolutional Auto-Encoder

Yarn-dyed Fabric Defect Detection using U-shaped De-noising ...

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Data Driven control and Learning Systems (DDCLS)

作者： Hong-wei Zhang Quan-lu Tan Shuai Lu Zhi-qiang Ge De Gu School of Electronic Information Xi’an Polytechnic University Xi’an China Institute of Industrial Process Control Zhejiang University Hangzhou China Institute of Mathematical Beijing University of Chemical Technology Beijing China Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Practical factors such as high labor cost of labelling defect samples and scarcity of defect samples make it difficult for supervised machine learning models to solve the problem of yarn-dyed fabric defect detection. To solve this problem, this paper proposes an unsupervised yarn-dyed fabric defect detection method based on U-shaped de-noising convolutional auto-encoder (UDCAE). Firstly, for tested samples of yarn-dyed fabric, the training dataset was constructed by collecting the non-defect yarn-dyed fabric samples. Then, the non-defect dataset is utilized to model and train the proposed UDCAE model. Finally, the defective area can be quickly detected by calculating the residual between the original tested yarn-dyed fabric image and its reconstructed item correspondingly. The experiment results show that the proposed method can accurately detect defects of yarn-dyed fabrics with different patterns.

关键词： Fabrics Image reconstruction Training Noise reduction Feature extraction Testing Inspection

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An Efficient Evolutionary Algorithm for High-Speed Train Rescheduling Under a Partial Station Blockage

SSRN

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SSRN 2023年

作者： Wang, Rongsheng Zhang, Qi Dai, Xuewu Yuan, Zhiming Zhang, Tao Ding, Shuxin Jin, Yaochu China Academy of Railway Sciences Corporation Limited Beijing100081 China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Train Operation Control Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing100081 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Faculty of Technology Bielefeld University BielefeldD-33615 Germany Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR model that is subject to train operation constraints is established to minimize the total train delay. The PS-SEGA framework consists of the following main steps. Firstly, a permutation-based encoding method is developed to define an efficient search space based on a train departure sequence. A decoding method is employed to output the rescheduled timetable and objective value based on the departure sequence. Moreover, a hybrid initialization method involving an efficient heuristic strategy (EHS) is put forward to accelerate the convergence speed of Evolutionary algorithms (EAs). Using problem-specific knowledge, EHS generates an efficient and feasible solution for the initial population. Finally, a restart strategy is presented to maintain genetic diversity. Compared with other advanced EAs and their improved variants also using the PS-SEGA framework, experimental results demonstrate the effectiveness of the proposed PS-SEGA for addressing HSTR scenarios under the partial station blockage. As for the scenarios that CPLEX can not obtain optimal solutions within 10 minutes, PS-SEGA can all provide quasi-optimal solutions in real-time. Furthermore, compared with the other two strategies (i.e., First-Scheduled-First-Served and EHS), PS-SEGA can find the best departure sequence that can output the timetable with a quasi-optimal solution. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

arXiv

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

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