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2020 International Conference on Information Science and Communications Technologies, ICISCT 2020

作者： Gazieva, Rano Aynakulov, Sharafidin Nigmatov, Aziz Rakhmankulova, Barna Khafizov, Otabek Ziyaeva, Sholpan Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Department of Automation and Control of Thechnology Process in Production Tashkent Uzbekistan Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Department of Information Technology Tashkent Uzbekistan

ISBN: (纸本)9781728199696

This article devoted to make characteristic of electrical engine on base of program platform PASCAL. In this paper consider and construct the mechanical characteristic of an induction motor, and calculate the main parameters of the electric motor. In the program compiled for this task, the voltage of loss of the starting ability with the rated torque on the shaft is calculated, the relationship between the slip and the motor torque is determined. © 2020 IEEE.

关键词： Induction motors

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An atraumatic mock loop for realistic hemocompatibility assessment of blood pumps

TechRxiv

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TechRxiv 2023年

作者： Bender, Moritz Escher, Andreas Röhrich, Michael Fischer, Michael Bernhard Hametner, Christoph Laufer, Günther Kertzscher, Ulrich Zimpfer, Daniel Jakubek, Stefan Granegger, Marcus The Department of Cardiac Surgery Medical University of Vienna Austria The Division of Control and Process Automation Institute of Mechanics and Mechatronics Vienna University of Technology Vienna1040 Austria Biofluid Mechanics Laboratory Berlin Germany The Division of Special Anesthesia and Pain Medicine Department of Anesthesia Intensive Care Medicine and Pain Medicine Medical University of Vienna Austria The Department for Blood Group Serology and Transfusion Medicine Medical University of Vienna Austria

Conventional mock circulatory loops (MCLs) cannot replicate realistic hemodynamic conditions without inducing blood trauma. This constrains in-vitro hemocompatibility examinations of blood pumps to static operating conditions that do not reflect clinical scenarios. This study aimed at developing an atraumatic MCL based on a hardware-in-the-loop concept (H-MCL) that enables hemocompatibility assessment under realistic hemodynamic conditions. The atraumatic H-MCL was designed for 450±50 ml of blood with the sole blood-contacting components being the polycarbonate reservoirs, the silicone/polyvinyl-chloride tubing and the blood pump under investigation. To account for inherent coupling effects a decoupling pressure control was derived by feedback linearization, whereas the level control was addressed by an optimization task to overcome periodic loss of controllability. The HeartMate 3 was showcased to evaluate the H-MCL’s accuracy at typical hemodynamic conditions and to demonstrate the H-MCL’s atraumatic properties. Pilot hemolysis experiments were conducted with bovine (n=2) and human (n=2) blood, and evaluated in terms of the normalized index of hemolysis (NIH). Typical hemodynamic scenarios of patients with full and partial support were replicated with marginal coupling effects and root mean square error (RMSE) of 1.74±1.37 mmHg and 0.94±0.83 mmHg, respectively, while the fluid level did not exceed a range of ±4% of its target value. The initial examinations of hemolysis demonstrated the atraumatic characteristics of the novel H-MCL, as evidenced by levels of NIH (bovine: 5.1-7.2mg/100L;human: 1.6-1.8mg/100L) that are consistent with those reported in existing literature. Collectively, these findings indicated the H-MCL’s potential for in-vitro hemocompatibiltiy assessment of blood pumps within realistic hemodynamic conditions. © 2023, CC BY.

关键词： Hemodynamics

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries

Exponential Weighted Moving Average-Based Variational Mode D...

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Data Driven control and Learning Systems (DDCLS)

作者： Penghao Wu Hongfeng Tao Engang Tian Tangwen Yin Hongtian Chen Yiyang Chen School of Mechanical and Electrical Engineering Soochow University Suzhou P. R. China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi P. R. China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai P. R. China Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods.

关键词： Fault diagnosis Learning systems Employee welfare Sensitivity Power supplies Noise Electric vehicles

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Quantized Distributed Nonconvex Optimization with Linear Convergence

Quantized Distributed Nonconvex Optimization with Linear Con...

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IEEE Conference on Decision and control

作者： Lei Xu Xinlei Yi Jiayue Sun Yang Shi Karl Henrik Johansson Tao Yang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering University of Victoria Victoria Canada

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper considers distributed nonconvex op-timization for minimizing the average of local cost functions, by using local information exchange over undirected communication networks. Since the communication channels often have limited bandwidth or capacity, we first introduce a quantization rule and an encoder/decoder scheme to reduce the transmission bits. By integrating them with a distributed algorithm, we then propose a distributed quantized nonconvex optimization algorithm. Assuming the global cost function satisfies the Polyak– Łojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that the proposed algorithm linearly converges to a global optimal point. Moreover, a low data rate is shown to be sufficient to ensure linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical simulation examples.

关键词： Quantization (signal) Communication channels Bandwidth Cost function Numerical simulation Communication networks Distributed algorithms

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids with Coupled Electricity-Hydrogen-Ammonia under Uncertainties

arXiv

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arXiv 2024年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2024, CC BY.

关键词： Ammonia

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Development of a Graph Model and Algorithm to Analyze the Dynamics of a Linear System with Delay

Development of a Graph Model and Algorithm to Analyze the Dy...

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Shakhnoza R. Ubaydulayeva Aziz M. Nigmatov Department “Automation and control of technology process in production” Tashkent institute of irrigation and agricultural mechanization engineers

ISBN: (数字)9781728145907

ISBN: (纸本)9781728145914

The article deals with the problem of modeling and calculating processes in a linear system with a delay based on dynamic graphs. A graph model of a continuous lagging signal (initial function) is constructed. A graph model of a linear stationary system with a delay in the feedback chain is constructed as a union of graph models of its elements. The graph model makes it obvious that a system with a delay in the feedback circuit is open relative to the signals flowing in it, which makes it possible to significantly simplify computational procedures. A linear system with a delayed control signal is also considered. Based on graph models the authors obtain the recurrent relations and an algorithm for calculating processes in a linear system with a delay in state and a delay in control. The paper presents an example of using the obtained algorithm. The proposed method allows for a clear and strict formalization of the description and analysis of complex systems, including nonlinear discrete systems with different types of modulation.

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A safe control scheme for the dense medium coal separation process based on Bayesian network and Active Learning

A safe control scheme for the dense medium coal separation p...

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第33届中国控制与决策会议

作者： Wenchao Bao Fei Chu Chao Shang Tao Chen Fuli Wang Furong Gao China University of Mining and Technology School of Information and Control EngineeringUnderground Space Intelligent Control Engineering Research Center of the Ministry of Education Department of Automation Tsinghua University Department ofChemistry and Process Engineering University of Surrey School of Information Science and Engineering Northeastern University Department of Chemical Engineering Hong Kong University of Science and Technology

The paper presents a safe control method for the operation of dense medium coal preparation process based on Bayesian network(BN) and active *** dense medium coal preparation process fluctuates significantly in operating conditions and abnormal operating conditions occur frequently due to the uncertainty in the *** address this issue,we establish the BN model of safety control by integrating qualitative expert knowledge and quantitative data information based on the analysis of causes of abnormal conditions and corresponding operation schemes,which acts as the basis for the safety *** the previous BN structure learning method based on observation data information can only get Markov equivalence class and needs a large amount of data,it is difficult to establish an accurate *** address this issue,we propose a BN structure learning method based on active learning to improve its efficiency and *** results show that the proposed method can effectively provide safety control decisions for abnormal conditions in the dense medium coal preparation process.

关键词： Safe control Bayesian network Active learning Dense medium coal separation

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Compressed Gradient Tracking Algorithms for Distributed Nonconvex Optimization

arXiv

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arXiv 2023年

作者： Xu, Lei Yi, Xinlei Wen, Guanghui Shi, Yang Johansson, Karl H. Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Systems Science School of Mathematics Southeast University Nanjing210096 China The Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

In this paper, we study the distributed nonconvex optimization problem, aiming to minimize the average value of the local nonconvex cost functions using local information exchange. To reduce the communication overhead, we introduce three general classes of compressors, i.e., compressors with bounded relative compression error, compressors with globally bounded absolute compression error, and compressors with locally bounded absolute compression error. By integrating them, respectively, with the distributed gradient tracking algorithm, we then propose three corresponding compressed distributed nonconvex optimization algorithms. Motivated by the state-of-the-art BEER algorithm proposed in [1], which is an efficient compressed algorithm integrating gradient tracking with biased and contractive compressors, our first proposed algorithm extends this algorithm to accommodate both biased and non-contractive compressors. For each algorithm, we design a novel Lyapunov function to demonstrate its sublinear convergence to a stationary point if the local cost functions are smooth. Furthermore, when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, we show that our proposed algorithms linearly converge to a global optimal point. It is worth noting that, for compressors with bounded relative compression error and globally bounded absolute compression error, our proposed algorithms’ parameters do not require prior knowledge of the P–L constant. The theoretical results are illustrated by numerical examples, demonstrating the effectiveness of the proposed algorithms in significantly reducing the communication burden while maintaining the convergence performance. Moreover, simulation results show that the proposed algorithms outperform the state-of-the-art compressed distributed nonconvex optimization algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

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Submodularity-based sensor scheduling for state estimation among multiple linear dynamical systems

Submodularity-based sensor scheduling for state estimation a...

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Jiangsu Annual Conference on automation (JACA 2022)

作者： Y. Ni C. Yang X. Liu X. Luan F. Liu The Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Engineering Jiangnan University Wuxi People's Republic of China The Key Laboratory of Smart Manufacturing in Energy Chemical Process (Ministry of Education) Department of Automation East China University of Science and Technology Shanghai People's Republic of China Department of Radiology Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital/Harvard Medical School Boston USA

In this paper we focus on the sensor scheduling for dynamic state estimation among multiple processes. Multiple sensors transmit their measurements to the remote estimator via a shared wireless channel. Only a subset of sensors are allowed to transmit at each time. The objective of the scheduler is to maximize a linear combination of the terminal time estimation error covariances in a log-determinant sense. We develop conditions under which the objective is monotone and submodular. A submodularity-based greedy scheduling algorithm is proposed, and its performance bound is provided. Numerical examples are presented to illustrate the theoretical findings.

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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