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SSRN 2024年

作者： Hong, Feng Wei, Kuanchang Ji, Weiming Hao, Junhong Fang, Fang Liu, Jizhen The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Energy storage systems, coupled with power sources, are applied as an important means of frequency modulation support for large-scale grid connection of new energy. Flywheel energy storage systems (FESS) are considered short-term energy storage solutions due to their capacity for rapid and efficient energy storage and release. However, the power output characteristic of flywheels is potentially correlated to the state of charge (SOC) in the process of continuous operation while the SOC distribution would be attributed to the output power and duration of the flywheel. This study theoretically developed analytical correlations between SOC distribution and flywheel dynamic characteristics on statistical performance based on a cross-entropy method under wide range sampling scenarios of SOC. The results demonstrate that various operation states of FESS have a disparity effect on the statistical performance of modules. A SOC management and capacity configuration method considering continuous operation states is proposed, and the results illustrate that the capital expenditure of capacity configuration cuts approximately 8.2% attaining the SOC stability under the homogenous frequency modulation scenario. Therefore, capacity configurations of FESS can effectively compensate for the capital loss caused by detrimental SOC so that the cross-entropy correlation method conducted in series has the capacity advantages. © 2024, The Authors. All rights reserved.

关键词： Flywheels

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A Summary of Research on Combustion Stability of Coal-fired Power Station Boilers

A Summary of Research on Combustion Stability of Coal-fired ...

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2021 China Automation Congress, CAC 2021

作者： Cai, Guoyuan Niu, Yuguang Liu, Xuefei State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781665426473

The research on the combustion stability of coal-fired power plant boilers is related to the safe operation and economic benefits of the boiler. The combustion stability judgement plays an important role for the assessment of flexibility retrofit with coal-fired power plants participating in deep peak-regulating operation. Therefore, the study of combustion stability judgment has always been a hot research direction. This paper briefly introduces the development history of boiler flame combustion stability research, and focuses on two popular research directions in this field in recent years, namely flame image combustion stability detection method and multiinformation fusion combustion Stability testing methods, briefly summarize the development trends of these two research directions and their respective advantages. Then, the current research status and problems in this field are put forward three aspects of thinking and suggestions. Finally, several problems that need to be solved in the future development of combustion stability research are summarized. © 2021 IEEE

关键词： Coal fired power plant

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Dynamic Random Route Mutation Mechanism for Moving Target Defense in SDN 6

Dynamic Random Route Mutation Mechanism for Moving Target De...

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6th International Symposium on computer and Information Processing Technology, ISCIPT 2021

作者： Zhang, Bofeng Han, Li Sun, Shimin Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin China Tiangong University Tianjin Key Laboratory of Autonomous Intelligent Technology and System School of Computer Science and Technology Tianjin China

ISBN: (纸本)9781665441377

Moving Target Defense (MTD) is commonly used in changing the asymmetric situation between attack and defense in cyberspace. Route mutation is a vital branch of MTD. Current route mutation methods still have some limitations on unpredictability of mutating routing paths and time overhead. In this paper, we propose a Dynamic Random Route Mutation (DRRM) mechanism in order to maximize the unpredictability of mutation and reduce the time overhead. First, we adopt Jaccard distance matrix and temporal constraint to improve mutation space. Mutation space can be dynamically shifted to enhance the unpredictability. Then, we weaken attackers' capabilities of launching effective eavesdropping at a certain node by using route weight. Finally, we construct a pre-distribution strategy to reduce the transmission latency caused by route mutation. Simulation results show that DRRM not only raises the difficulty of network eavesdropping, but also ensures low mutation time overhead. © 2021 IEEE.

关键词： Dynamics

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Design and Validation of Flexible Aerial Robotics for Safe Human-Robot Interaction

Design and Validation of Flexible Aerial Robotics for Safe H...

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

作者： Fuhua Jia Zihao Zheng Cheng’ao Li Junlin Xiao Rui Li Xiaoying Yang Adam Rushworth Salman Ijaz Department of Mechanical Materials and Manufacturing and Members of Control System Laboratory University of Nottingham Ningbo China Ningbo Innovation Center Zhejiang University School of Applied Physics and Electronics Umea University School of Computer Science University of Nottingham Ningbo China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This work addresses the critical challenge of integrating drones into human-aerial robot interaction by presenting a novel Soft Flexible Aerial Robotics (SFAR) design. SFAR features an innovative low-pressure inflatable airbag structure that replaces traditional rigid frames, enhancing safety by mitigating collision risks with humans and payloads. To control this unconventional aerial platform, we present a control strategy based on a virtual link dynamics model that exploits the drone’s unique design. Our contributions include the pioneering design of an aerial robot specifically for Human-Aerial Robot Interaction (HARI), a novel control framework that balances flight performance with passive safety, and the validation of SFAR through real-world experiments, demonstrating its ability to perform at par with traditional rigid-body drones while offering enhanced safety features for seamless and safe integration into human environments.

关键词： Virtual links Navigation Atmospheric modeling Human-robot interaction Safety Collision avoidance Flexible structures Intelligent robots Drones Payloads

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Multi-Resolution Planar Region Extraction for Uneven Terrains

arXiv

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arXiv 2023年

作者： Sun, Yinghan Zheng, Linfang Chen, Hua Zhang, Wei Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Computer Science University of Birmingham United Kingdom

This paper studies the problem of extracting planar regions in uneven terrains from unordered point cloud measurements. Such a problem is critical in various robotic applications such as robotic perceptive locomotion. While existing approaches have shown promising results in effectively extracting planar regions from the environment, they often suffer from issues such as low computational efficiency or loss of resolution. To address these issues, we propose a multi-resolution planar region extraction strategy in this paper that balances the accuracy in boundaries and computational efficiency. Our method begins with a pointwise classification preprocessing module, which categorizes all sampled points according to their local geometric properties to facilitate multi-resolution segmentation. Subsequently, we arrange the categorized points using an octree, followed by an in-depth analysis of nodes to finish multi-resolution plane segmentation. The efficiency and robustness of the proposed approach are verified via synthetic and real-world experiments, demonstrating our method’s ability to generalize effectively across various uneven terrains while maintaining real-time performance, achieving frame rates exceeding 35 FPS. Copyright © 2023, The Authors. All rights reserved.

关键词： Computational efficiency

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Predictor-Based Constrained Fixed-Time Sliding Mode control of Multi-Uav Formation Flight

SSRN

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SSRN 2024年

作者： Khodaverdian, Maria Hajshirmohamadi, Shahram Hakobyan, Aleksandr Ijaz, Salman Center for Scientific Innovation and Education Aerial Robotics Laboratory of National Polytechnic University of Armenia Yerevan Armenia Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Key Laboratory of More Electric Aircraft and Control System Lab University of Nottingham Ningbo China

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicles formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational ***, a constrained performance index is constructed based on the prediction of the fixed-time sliding surface, the reaching law, and the control input. Secondly, optimal control input is calculated by solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop system stability in the presence of external disturbances and ***, the comparative evaluation with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, a test is conducted to demonstrate the algorithm's potential for hardware implementation by employing Hardware-in-the-Loop (HIL) test. © 2024, The Authors. All rights reserved.

关键词： Sliding mode control

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A LiDAR-Assist Yaw Misalignment Compensation Method Based on Machine Learning Algorithms

A LiDAR-Assist Yaw Misalignment Compensation Method Based on...

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Chinese control Conference (CCC)

作者： Pei Chen Zhongwei Lin Zihan Zhang Zhen Xie State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing P. R. China

Yaw misalignment is common in the yaw system control of wind turbines, resulting in reduced power generation efficiency and increased load. The advantage of LiDAR is that the accuracy of wind measurement is greatly improved, while its disadvantage is that the cost remains high. In this paper, an efficient machine learning method for estimating LiDAR measurement, XGBoost, is used to establish the data-driven wind turbine yaw misalignment compensation framework. To choose a suitable algorithm, four machine learning algorithms are studied, namely Linear Regression, Random Forest, Gradient Boosting and XGBoost. Moreover, to verify the effectiveness of the proposed method, a 2MW WT was taken as the research object for filed testing, and the power generation was quantitatively evaluated under the three strategies of wind vane control, LiDAR control and ML algorithm control. The results show that the proposed yaw misalignment compensation method is feasible for field application. In this way, the yaw-to-wind error can be mitigated even after the LiDAR is removed.

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MPC Implementation for Optimal Active Power control of Large-Scale Wind-PV-Battery Hybrid system

MPC Implementation for Optimal Active Power Control of Large...

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Chinese control Conference (CCC)

作者： Zihan Zhang Zhongwei Lin Ze Zhao Jiawei Zhou Chenzhi Qu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing P. R. China

This paper investigates the operational strategy for real-time optimal active power control of large-scale wind-PV-battery hybrid system. The MPC strategy is established with objective, forecast models and constraints for active power control of wind-PV-battery hybrid system, which simultaneously maximizes tracking accuracy and minimizes settling time. To guarantee the industrial reliability, the corresponding optimization solver and control architecture have been specifically developed and designed. Hardware-in-loop (HIL) experiments are conducted using the real-time digital simulator (RTDS) and programmable logic controllers (PLCs). Under different operating scenarios, HIL-RTDS testing results demonstrate that the MPC strategy significantly improves the tracking speed and accuracy compared to the conventional strategy in both normal and abnormal operating scenarios, which also sustain the feasibility of industrial implementation.

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Game Learning-Based Target Allocation of the UAV Confrontation system

Game Learning-Based Target Allocation of the UAV Confronta...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Hu, Yaxu Zhang, Yanling Xiao, Feng Key Laboratory of Intelligent Bionic Unmanned Systems School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 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)9789819622313

Previous studies on the UAV swarm air combat decision-making problem lack consideration of uncertainty, intense confrontation, and high dynamics of aerial combat scenarios. This paper delves into the target allocation decision problem of the UAV attack and defense confrontation in a dynamic aerial combat environment. First, a dynamic game model is proposed to adapt changes in combat resources and adversaries’ behavior throughout multi-stage game processes. Then, the corresponding Nash equilibrium is solved based on a game learning algorithm- the Q-Learning algorithm. Finally, we consider the case where the UAV destructive probability is unknown, an uncertainty model is designed for predicting the UAV destructive probability based on the fuzzy comprehensive evaluation method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fuzzy comprehensive evaluation game learning target allocation UAV swarm

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ESNet: evolution and succession network for high-resolution salient object detection 24

ESNet: evolution and succession network for high-resolution ...

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Proceedings of the 41st International Conference on Machine Learning

作者： Hongyu Liu Runmin Cong Hua Li Qianqian Xu Qingming Huang Wei Zhang Institute of Information Science Beijing Jiaotong University & Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University & Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature; the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24.

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