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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Tianyu Zhang Kedi Zheng Qixin Chen Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China

With the proposal of carbon peaking and carbon neutrality goals, the proportion of renewable energy generation continues to increase and the number of new photovoltaic power stations is growing rapidly. Accurate photovoltaic power prediction is of great significance for the safe, stable and operation of power system. In order to solve the problem of insufficient historical data of newly constructed PV power plants, this paper proposes a short-term PV power prediction model based on Long Short Term Memory and transfer learning. The model uses meteorological data, numerical weather forecast data and PV power as features. According to the transfer learning theory, the Long Short Term Memory model is pre-trained using the historical data of other previously-built PV power plants, and then a small amount of local operation data is used to fine-adjust the model. Case study based on Hebei open source photovoltaic and meteorological data set proves that the proposed transfer learning model can effectively improve the short-term PV power prediction accuracy, and the MAPE can be improved by up to 15%.

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A Comparing Study on Assessment Mechanism for Renewable Energy Bidding Deviation in Spot Trading 5

A Comparing Study on Assessment Mechanism for Renewable Ener...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Wang, Hao Zhang, Li Guo, Yixin Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China North China Electric Power University School of Electrical and Electronic Engineering Baoding China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Participating in market trading is an essential step to promote the sustainable development of renewable energy. To properly deal with the uncertainty of renewable energy, it is important to establish a reasonable bidding deviation assessment mechanism in the electricity market. Based on the analysis of existing research and practice, the bidding deviation assessment mechanism are summarized into two categories, that is, the outcome assessment mechanism (OAM) and the performance assessment mechanism (PAM). Models of the mechanism are built to analyze the principles of the two types of mechanism, and the impact of aggregation effect of renewable energy on the assessment is discussed. Simulation results show that the outcome assessment mechanism will lead to over-assessment, but is conducive to motivating renewable energy stations (RSs) to actively reduce bidding deviation;while the performance assessment mechanism can ensure the cost-recovering of balancing dispatch, but make RSs unable to improve market behavior except to passively accept penalties at settlement. To promote the development of renewable energy, both assessment mechanisms have room for further improvement. © 2022 IEEE.

关键词： Power markets

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Applying system Thinking to Learn from Accident of Modern Automatic control systems

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Chinese Journal of Electronics 2025年第2期23卷 409-414页

作者： Ru Niu Yuan Cao Xiaocheng Ge Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronics and Information Engineering National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Department of Computer Science University of York York UK

Modern societies increasingly rely on automatic control systems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events, rather than a simple cause-effect chain. We take railway Train control systems (TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP - one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.

关键词： Sociotechnical systems Analytical models systematics Railway accidents Transportation Medical services Rail transportation systems thinking Research and development Accidents

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SoftNeRF: A Self-Modeling Soft Robot Plugin for Various Tasks

SoftNeRF: A Self-Modeling Soft Robot Plugin for Various Task...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jiwei Shan Yirui Li Qiyu Feng Ditao Li Lijun Han Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Building a self-model for robots, enabling them to simulate their physical selves and predict future states without direct interaction with the physical world, is crucial for robot motion planning and control. Existing self-modeling methods primarily focus on rigid robots and typically require significant time, effort, and resources to gather training data. In this study, we introduce SoftNeRF, a self-supervised visual self-model designed for soft robots. We use a hybrid neural shape representation based on the Signed Distance Function (SDF) to capture both the geometry and complex nonlinear motion of soft robots. By leveraging differentiable rendering, our method learns a self-model from readily available RGB images, similar to how humans understand their physical state through reflection. To improve training efficiency and model accuracy, we propose an error-guided adaptive sampling strategy. SoftNeRF can serve as a plug-in for various downstream tasks, even when trained with data unrelated to those tasks. We demonstrate SoftNeRF’s ability to support shape prediction and motion planning for robots in both simulated and real-world environments. Furthermore, SoftNeRF excels in detecting and recovering from damage, thereby enhancing machine resilience. Code is available at: https://***/irmvlab/soft-nerf.

关键词： Training Visualization Adaptation models Accuracy Shape Training data Soft robotics Rendering (computer graphics) Sampling methods Planning

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Integrated Capacity Analysis Model and Optimization Based on Conflict Resolution for High-Speed Railway

Integrated Capacity Analysis Model and Optimization Based on...

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2022 Chinese Automation Congress, CAC 2022

作者： Wei, Yuan Ma, Lin Yin, Jiateng Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing100044 China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing100044 China

ISBN: (纸本)9781665465335

With the increased demand of passengers, the capacity analysis of high-speed railways has attracted much attention for serving more passengers with limited line resources. Existing methods mainly focused on the capacity analysis of rail sections or stations, separately. Our study first addressed the integrated capacity analysis of high-speed railways. We established an integrated capacity analysis model by combining the signal control of track sections, the overtaking of trains and the capacity of rail stations. Then this paper proposed a conflict resolution strategy based on multi-objective optimization. A real-world case study on the Beijing-Shanghai high-speed railway demonstrated that our approach can better model the influencing factors in high-speed railways and can further improve the line capacity compared with existing approaches. © 2022 IEEE.

关键词： Multiobjective optimization

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TSN-compatible Industrial Wired/Wireless Multi-protocol Conversion Mechanism and Module 48

TSN-compatible Industrial Wired/Wireless Multi-protocol Conv...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Chen, Yingxiu Xu, Qimin Zhang, Jinglong Xu, Lei Li, Lingzhi Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

The interoperability of heterogeneous networks, including hybrid industrial wired/wireless protocols, is a vital aspect of the Industrial Internet of Things (IIoT) since various industrial protocols have coexisted. Therefore, it is hard to obtain a multiple protocol conversion solution with the flexible configuration. Moreover, the previous works do not adapt to the Time Sensitive Networking (TSN), which is considered as the potential technology of IIoT. To tackle the above problems, we proposed an architecture of the multiple conversion system supporting the conversion of multiple protocols. Then, we proposed a protocol conversion mechanism to improve the flexibility of multiple protocol conversion by separating into data and configuration planes. Moreover, we propose a TSN-compatible frame with dynamic priority mapping algorithm, which adjusts the priority in the VLAN tag by the processing delay. Finally, we develop a hardware module and system supporting multiple protocol conversion, which verify that the proposed architecture could satisfy the flexible conversion requirement through the experiments. © 2022 IEEE.

关键词： Ethernet

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DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscopic Scenes

DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscop...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jiwei Shan Yirui Li Lujia Yang Qiyu Feng Lijun Han Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Estimating camera motion and continuously reconstructing dense scenes in deformable environments presents a complex and open challenge. Many existing approaches tend to rely on assumptions about the scene’s topology or the nature of deformable motion. However, these assumptions do not hold true in medical endoscopy applications. To address these challenges, we introduce DDS-SLAM, a novel dense deformable semantic neural SLAM that achieves accurate camera tracking, continuous dense scene reconstruction, and high-quality image rendering in deformable scenes. First, we propose a novel hybrid neural scene representation method capable of capturing both natural and artificial deformations. Additionally, by leveraging the 2D semantic information of the scene, we introduce a semantic loss function based on semantic distance fields. This approach guides network optimization at a higher level, thereby enhancing system performance. Furthermore, we validate our method through a series of experiments conducted on several representative medical datasets, demonstrating its superiority over other state-of-the-art approaches. The code is available at: https://***/IRMVLab/DDS-SLAM.

关键词： Simultaneous localization and mapping Tracking system performance Semantics Cameras Rendering (computer graphics) Topology Image reconstruction Optimization Biomedical imaging

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Optimal Design of Full-Bridge Three-Level LLC Converter Based on Time-Domain Analysis

Optimal Design of Full-Bridge Three-Level LLC Converter Base...

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Power Electronics and Application Symposium (PEAS), IEEE International

作者： Zengyang Liu Kai Sun Zheyuan Yi Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China

Fully DC wind turbine generator system is a promising substitute for conventional AC one. In the system, the LLC step-up converter plays a key role. Mode analysis and time-domain expressions can provide more accurate estimation of the resonant performance than the conventional First Harmonic Analysis method. The circuit works at different modes as the load rate varies. This paper categorizes these resonant behaviors into four modes, with time-domain expressions of each mode obtained. The variation regular of these modes is given and is applied in the program to realize recognizing the working mode automatically. The simulation and experiment have verified the effectiveness of the proposed method.

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A Nonlinear Disturbance Observer Based on Sliding Mode control for a Lower Limber Exoskeleton Robot 7

A Nonlinear Disturbance Observer Based on Sliding Mode Contr...

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7th Asia-Pacific Conference on Intelligent Robot systems, ACIRS 2022

作者： Luo, Wenbo Liu, Haokun Yang, Xishun Zhang, Sen Ge, Weimin Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering Education School of Mechanical Engineering Tianjin300384 China

ISBN: (数字)9781665485197

ISBN: (纸本)9781665485197

During the process of human-robot cooperative motion, the internal frictions and modeling errors existing in the system may significantly deteriorate the control precision of a lower limb exoskeleton. To compensate the uncertainty during the human-robot cooperative motion, a nonlinear disturbance observer based sliding mode control strategy is designed in this paper. Firstly, the dynamic model of a lower limb exoskeleton is established. Secondly, low-pass filter and nonlinear disturbance observer are designed to observe the uncertain disturbance and modeling errors. Then, a high-order sliding mode controller is designed to ensure the control precision of the human-robot interaction system. Finally, the effectiveness and reliability of the designed control method are verified with the joint simulation between MATLAB and ADAMS. © 2022 IEEE.

关键词： Sliding mode control

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Optimal Design for the Torsional Elastic Element Topology of a Rotary Series Elastic Actuator 7

Optimal Design for the Torsional Elastic Element Topology of...

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7th Asia-Pacific Conference on Intelligent Robot systems, ACIRS 2022

作者： Yang, Xishun Luo, Wenbo Liu, Haokun Zhang, Sen Ge, Weimin Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering Education School of Mechanical Engineering Tianjin300384 China

ISBN: (数字)9781665485197

ISBN: (纸本)9781665485197

The series elastic actuator improves the compliance of exoskeleton by introducing a elastic element and ensures its safe interaction ability. Therefore, it is regarded as a new driving mechanism by scholars. Suitable elastic element is conducive to realize the miniaturization and lightweight of SEA, but its topology design is complex and lack of guidance. Based on the finite element simulation environment and three-dimensional parametric CAD environment, this paper analyzes the influence of different size parameters and topology on the pressure of the elastic element, summarizes the characteristics of three topology structures, and puts forward the optimal design method of a torsional elastic element topology. Through the research, we can conclude that the compression effect of elastic beam with specific shape is better than that of curved elastic beam, and the width of elastic beam has a great influence on the torsional elastic element. © 2022 IEEE.

关键词： Finite element method

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