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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Lu, Yu Liu, Yiqi Li, Dong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Technical University of Denmark Department of Chemical and Biochemical Engineering Lyngby Denmark

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Process monitoring of operation cost index (OCI) is of great importance for wastewater treatment plants (WWTPs), which is not only able to support financial budget, but also to optimize local operation. This paper proposed four variants of auto-regressive and moving average (ARMA), based on recursive least squares algorithm (RLS), ARMA based on recursive extended least squares algorithm (RELS), nonlinear auto-regressive neural network (NARNN), and nonlinear auto-regressive neural network with external input (NARXNN) respectively, to predict the operating cost in WWTPs. The proposed methods were validated in the simulation platform, Benchmark Simulation Model No.2-P (BSM2-P). On account of the strong nonlinearity of the wastewater treatment process, the nonlinear model, like NARXNN, achieved better performance in terms of mean square error (MSE) and correlation coefficient (R). © 2022 IEEE.

关键词： Wastewater treatment

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IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using Wheel-Encoder and Inertial-RGB-Depth Measurements 30

IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using ...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Liu, Yuanhao Liang, Wei Wang, Chu Zhang, Xin Gao, Huanbing Zhang, Yinlong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Information and Electrical Engineering Shandong Jianzhu University Jinan China Shandong Key Laboratory of Intelligent Buildings Technology Jinan China

ISBN: (纸本)9798350391916

Safe & smart move (SSM) aims to help industrial vehicular robot (IVR), such as warehousing robots, running safely and smartly by detecting the obstacles in front and maintaining a safe distance & attitude. However, the traditional SSM methods suffer the drawbacks of limited ranges, inaccurate regression of safety distance & orientation between the robot and the forward unexpected obstacles, and the inappropriate IVR control strategies. To solve these issues, this paper designs an innovative real-time safety-aware framework using the complementary Wheel-Encoder and Inertial-RGB-Depth measurements to ensure the IVR running safely, reasonably and reliably. To estimate the robot running states, we take advantages of the complementary wheel encoder, monocular RGB images and inertial measurements to obtain the robot positions, orientations, angular and linear velocities in a tightly-coupled manner. To improve the safety relative distance & attitude estimation accuracy, we exploit the RGB and depth measurements in a task-oriented fashion. The forward obstacles with the specific contours are detected using the Mask-RCNN model, followed by the Gaussian Mixture Model to obtain the forward obstacle depth. Eventually, an IVR control strategy is designed to maintain the robot safety distance and orientation, and to keep the minimum damage to the robot mechanical system. The presented method has been evaluated on the developed industrial vehicular robot safety perception platform. The experimental results prove the competitiveness against the state-of-the-art methods. © 2024 IEEE.

关键词： Industrial robots

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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Performance comparison for grid connected photovoltaic system using sliding mode control

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Journal of King Saud University - engineering Sciences 2021年第4期33卷 276-283页

作者： Menaga, D. Sankaranarayanan, V. Department of Electrical and Electronics Engineering National Institute of Technology Control Systems Research Laboratory Tiruchirappalli620 015 India

Three sliding mode controllers are designed for the control of a photo-voltaic system connected to grid on the nonlinear behavior of the dc-link capacitor and inverter switching input signals. In this proposed system, a nonlinear state space model is used after abc-dq reference frame transformation to design sliding mode control inputs to ensure the maximum power point extraction from the photo-voltaic system and unity power factor in the grid with different sliding manifolds. The performance of three sliding mode controller is compared and it is concluded that the controller based on the power balanced perform better compared to separate current and voltage tracking. Performance of these controller under nominal conditions, parameter variations and load disturbances is validated by the numerical simulation. © 2020

关键词： Sliding mode control

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Multi-agent Deep Reinforcement Learning Based Multi-objective Charging control for Electric Vehicle Charging Station 7th

Multi-agent Deep Reinforcement Learning Based Multi-objectiv...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Bearing Fault Diagnosis Under Variable Working Conditions Based on Domain Adaptation and Improved Depthwise Separable Convolution Network 26

Bearing Fault Diagnosis Under Variable Working Conditions Ba...

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26th International Conference on Industrial technology, ICIT 2025

作者： Kuang, Zehui Mao, Fan Zhao, Xingyu Wan, Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Domain adaptation methods and appropriate feature extractors are usually applied to solve the problem that the variable working conditions of bearings affect the effectiveness of the fault diagnostic framework. However, the existing feature extractors are too complex to be deployed in real industries. In this paper, we propose a lightweight framework called improved depthwise separable convolution network (IDSCN) for the diagnosis of bearing faults in variable operating conditions. IDSCN is built on wavelet convolution and depthwise separable residual convolution (DSRC), where the wavelet convolution is used to extract frequency features from the source and target domains, and DSRC guarantees the performance of feature extraction with reduced parameters and computation. To minimise the distribution difference between the source and target domains, the local maximum mean difference is incorporated into the proposed framework. The performance of the proposed framework is validated on the Paderborn University dataset, involving a total of 6 transfer tasks. The experiment shows that the proposed framework achieves satisfactory results and outperforms other frameworks in bearing fault diagnosis. © 2025 IEEE.

关键词： Bearing fault diagnosis Depthwise separable residual convolution Domain adaptation Wavelet convolution

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Simulated Ising Annealing Algorithm with Gaussian Augmented Hamiltonian Monte Carlo

Simulated Ising Annealing Algorithm with Gaussian Augmented ...

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第42届中国控制会议

作者： Langyu Li Hao Wang Zhixin Xie Zixuan Liu Wei Cui Yu Pan Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control TechnologyCollege of Control Science and Engineering Zhejiang University School of Automation Science and Engineering South China University of Technology School of Mechanical Engineering and Automation Harbin Institude of Technology

A numerical technique called Simulated Ising Annealing(SIA) uses digital computers to obtain approximations of the ground states of Ising models. The quadratic unconstrained binary optimization(QUBO) problem in combinatorial optimization,which is challenging to solve through exhaustive search, has significant linkages to the Ising model. Therefore, SIA's main objective is to identify a better solution in finite iterations. In order to enhance the performance of the simulated annealing procedure, we adopt a Gaussian augmented Hamiltonian Monte Carlo(GAHMC) method in this study. We contrasted our algorithm with Gibbs sampling and local quantum annealing method. Finally, we discuss its application on QUBO problem.

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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Simulation and Analysis of PMSM with Segmented Halbach Magnet Array

Simulation and Analysis of PMSM with Segmented Halbach Magne...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Ge, Lijia Yan, Liang Xiang, Pengjie Zhou, Yuchen Aboelhassan, Ahmed School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China Electrical and Control Engineering Department College of Engineering and Technology Arab Academy for Science Technology and Maritime Transport Alexandria1029 Egypt Key Laboratory of More Electric Aircraft Technology of Zhejiang Province University of Nottingham Ningbo China Ningbo315100 China

ISBN: (纸本)9789811966125

This paper investigates the relationship between the output performance of PMSM and the number of the Halbach magnetic segments. The static magnetic simulation models of the Halbach with three to seven segments are established, and the spatial harmonic distribution of these magnetic arrays under the static magnetic field is analyzed. The simulation date indicates that the five-segment configuration has the best suppression effect on the 5th harmonic, and the seven-segment Halbach magnet array has the maximum fundamental amplitude of magnetic flux density. Then, the transient magnetic simulation models of these magnetic configuration are established by FEM, and the dynamic performance in PMSM is simulated and analyzed. By comparing the simulation data, it indicates that the electromagnetic output performance of five-segment magnetic configuration is the best. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Harmonic analysis

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Modeling and Calculation of Temperature Field in Slotless Motor Based on a New Lumped Parameter Thermal Network Method 26

Modeling and Calculation of Temperature Field in Slotless Mo...

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26th International Conference on Electrical Machines and systems, ICEMS 2023

作者： Zhao, Jing Guo, Penglei Zheng, Yun Wang, You Yang, Lei Beijing Institute of Technology School of Automation Beijing China Beijing Aerospace Control Instrument Research Institute Department of Motor Power Supply Beijing China Beijing Institute of Control Engineering Beijing Key Laboratory of Long-life Technology of Precise Rotation and Transmission Mechanisms Beijing China

ISBN: (纸本)9798350317589

In order to achieve accurate analysis of the motor temperature field, the temperature field of the slotless motor is modeled and calculated based on the centralized parametric thermal network method. The distribution of the motor thermal network nodes is given, and the axial model of the motor is divided. By deriving the thermal resistance model of each component of the slotless motor, a full-domain thermal resistance network model of the motor is constructed, and the accuracy of the model is verified by comparing the results with the finite element simulation. © 2023 IEEE.

关键词： Finite element method

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