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Distributionally Robust Day-ahead Scheduling for Power-traffic Network under a Potential Game Framework

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arXiv 2022年

作者： Deng, Haoran Yang, Bo Ning, Chao Chen, Cailian Guan, Xinping The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Widespread utilization of electric vehicles (EVs) incurs more uncertainties and impacts on the scheduling of the power-transportation coupled network. This paper investigates optimal power scheduling for a power-transportation coupled network in the day-ahead energy market considering multiple uncertainties related to photovoltaic (PV) generation and the traffic demand of vehicles. The crux of this problem is to model the coupling relation between the two networks in the day-ahead scheduling stage and consider the intra-day spatial uncertainties of the source and load. Meanwhile, the flexible load with a certain adjustment margin is introduced to ensure the balance of supply and demand of power nodes and consume the renewable energy better. Furthermore, we show the interactions between the power system and EV users from a potential game-theoretic perspective, where the uncertainties are characterized by an ambiguity set. In order to ensure the individual optimality of the two networks in a unified framework in day-ahead power scheduling, a two-stage distributionally robust centralized optimization model is established to carry out the equilibrium of power-transportation coupled network. On this basis, a combination of the duality theory and the Benders decomposition is developed to solve the distributionally robust optimization (DRO) model. Simulations demonstrate that the proposed approach can obtain individual optimal and less conservative strategies. © 2022, CC BY-NC-SA.

关键词： Electric loads

Pseudo-LiDAR for Visual Odometry

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arXiv 2022年

作者： Deng, Huiying Wang, Guangming Feng, Zhiheng Jiang, Chaokang Wu, Xinrui Miao, Yanzi Wang, Hesheng Advanced Robotics Research Center AI Research Institute School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China 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 Shanghai200240 China

As one of the important tasks in the field of robotics and machine vision, LiDAR/visual odometry provides tremendous help for various applications such as navigation, location, etc. In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images. In this paper, the concept of pseudo-LiDAR is introduced into the odometry to solve this problem. The pseudo-LiDAR point cloud back-projects the depth map generated by the image into the 3D point cloud, which changes the way of image representation. Compared with the stereo images, the pseudo-LiDAR point cloud generated by the stereo matching network can get the explicit 3D coordinates. Since the 6 Degrees of Freedom (DoF) pose transformation occurs in 3D space, the 3D structure information provided by the pseudo-LiDAR point cloud is more direct than the image. Compared with sparse LiDAR, the pseudo-LiDAR has a denser point cloud. In order to make full use of the rich point cloud information provided by the pseudo-LiDAR, a projection-aware dense odometry pipeline is adopted. Most previous LiDAR-based algorithms sampled 8192 points from the point cloud as input to the odometry network. The projection-aware dense odometry pipeline takes all the pseudo-LiDAR point clouds generated from the images except for the error points as the input to the network. While making full use of the 3D geometric information in the images, the semantic information in the images is also used in the odometry task. The fusion of 2D-3D is achieved in an image-only based odometry. Experiments on the KITTI dataset prove the effectiveness of our method. To the best of our knowledge, this is the first visual odometry method using pseudo-LiDAR. Copyright © 2022, The Authors. A

关键词： Pipelines

Exploring single atom catalysts of transition-metal doped phosphorus carbide monolayer for HER:A first-principles study

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Journal of Energy Chemistry 2021年第1期30卷 155-162,I0006页

作者： Dachang Chen Zhiwen Chen Xiaoxing Zhang Zhuole Lu Song Xiao Beibei Xiao Chandra Veer Singh School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina Department of Materials Science and Engineering University of TorontoToronto M5S 3E4OntarioCanada Department of Mechanical and Industrial Engineering University of TorontoToronto M5S 3G8OntarioCanada Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068HubeiChina School of Energy and Power Engineering Jiangsu University of Science and TechnologyZhenjiang 212003JiangsuChina

Hydrogen has been identified as one of the most promising sustainable and clean energy. Developing hydrogen evolution reaction(HER) catalyst with high activity is essential for satisfying the future requirements. Considering novel advantages of two-dimensional materials and high catalytic activity of atomic transition metal, in this study, using density functional theory calculation, the HER on single transitionmetal(23 different TM atoms) doped phosphorus carbide monolayer(α-PC) has been investigated. The Volmer–Tafel and Volmer–Heyrovsky reaction mechanisms, and the stability of the most promising HER catalyst are also included. The results show that Ir-αPC with high physical and thermal stability has the most optimal value of Gibbs free adsorption energy for H atom. The relationship of d band center and the HER activity shows a volcano-like curve. The calculation of reaction energy barrier indicates that the Volmer-Heyrovsky step is more favorable than the Volmer-Tafel step.

关键词： Hydrogen evolution reaction Phosphorus carbide monolayer Transition-metal doping Density functional theory

Frequency Perception Network for Camouflaged Object Detection

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arXiv 2023年

作者： Cong, Runmin Sun, Mengyao Zhang, Sanyi Zhou, Xiaofei Zhang, Wei Zhao, Yao School of Control Science and Engineering Key Laboratory of Machine Intelligence and System Control Ministry of Education Shandong University Jinan Shandong China School of Automation Hangzhou Dianzi University Zhejiang Hangzhou China Institute of Information Science Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China

Camouflaged object detection (COD) aims to accurately detect objects hidden in the surrounding environment. However, the existing COD methods mainly locate camouflaged objects in the RGB domain, their performance has not been fully exploited in many challenging scenarios. Considering that the features of the camouflaged object and the background are more discriminative in the frequency domain, we propose a novel learnable and separable frequency perception mechanism driven by the semantic hierarchy in the frequency domain. Our entire network adopts a two-stage model, including a frequency-guided coarse localization stage and a detail-preserving fine localization stage. With the multi-level features extracted by the backbone, we design a flexible frequency perception module based on octave convolution for coarse positioning. Then, we design the correction fusion module to step-by-step integrate the high-level features through the prior-guided correction and cross-layer feature channel association, and finally combine them with the shallow features to achieve the detailed correction of the camouflaged objects. Compared with the currently existing models, our proposed method achieves competitive performance in three popular benchmark datasets both qualitatively and quantitatively. The code will be released at https://***/rmcong/FPNet_ACMMM23. © 2023, CC BY-NC-SA.

关键词： Frequency domain analysis

An Improved Safe Braking Model of Virtually Coupled Trains for Closer Tracking

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An Improved Safe Braking Model of Virtually Coupled Trains f...

IEEE International Conference on Networking, Sensing and control

作者： Wenxiao Yan Jiayu Wang Liqun Fan Qiusheng Liu Qingdong Jia Yihan Wang Hongjie Liu School of Automation and Intelligence Beijing Jiaotong University Beijing China Shenzhen Metro Group Co. Ltd. Shenzhen China Shenzhen Municipal Design and Research Institute Co. Ltd. Shenzhen China Traffic control Technology Co. Ltd. Beijing China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

With the rapid growth of transportation passenger flow in recent years, the research direction of Virtual Coupling (V C) in railways has become hot. V C increases capacity by tracking shorter distances. The traditional train emergency braking (EB) model can no longer meet the high operating efficiency requirements of VC. VC urgently needs a more efficient safety EB model. Therefore, to improve efficiency, a measurement of the EB model's rationality is defined considering safety and efficiency. Based on the defined model measurement, an EB model optimization method and a new EB model are proposed. The new model is closer to the actual braking process of the train and ensures safety from the distance level. That is, the braking trajectory of the train calculated by the new model is closer to the actual braking trajectory of the train, and the two braking trajectories satisfy the specific safety constraints. Finally, the safety and efficiency of the new model were verified through simulation experiments. The new model can avoid train collisions during the entire EB process. Experimental results show that compared with the traditional old EB model of VC based on space-time interval [1], the new model's minimum safe distance (MSD) between two VC train units can be reduced by 39%.

关键词： Couplings Analytical models Optimization methods Transportation Process control Safety Trajectory Sensors Brakes

GPIO Based Iterative Learning control for Manipulators with Time-Varying Disturbances

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GPIO Based Iterative Learning Control for Manipulators with ...

Chinese control Conference (CCC)

作者： Huangyuwei Lu Zuo Wang Jiankun Sun Xi Xiao Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Nanjing China Shenzhen Research Institute Southeast University Shenzhen China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing China

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators, a composite iterative learning control (ILC) scheme via generalized proportional integral observer (GPIO) is proposed. A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics, parameter uncertainties and load fluctuations. A GPIO is then designed to estimate the disturbances and high-order time derivatives. By introducing estimations into a PD-type ILC at each iteration, a composite control scheme is obtained, such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of manipulators. In this paper, the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to infinity. The effectiveness of the proposed control scheme is finally verified by simulation results.

关键词：

A Review of Integrated Optimization Method of Batch Planning and Scheduling for Steelmaking-Continuous Casting-Hot Rolling Production Under Uncertain Environment Based on Lagrangian Relaxation Framework

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Complex system Modeling and Simulation 2024年第4期4卷 387-401页

作者： Liangliang Sun Xirang Hao Yunpeng Li Jinghan Xue Natalia M.Matsveichuk Yuri N.Sotskov Qichun Zhang School of Control Engineering Northeastern University at QinhuangdaoQinhuangdao 066004China Sydney Smart Technology College Northeastern UniversityQinhuangdao 066004China Department of Production Management Automation System Belarusian Stage Agrarian Technical UniversityMinsk 220012Belarus United Institute of Informatics Provlems National Academy of Sciences of BelarusMinsk 220012Belarus Buckinghamshire New University High Wycombe HP13UK

The integrated process of steelmaking,continuous casting,and hot rolling(SM-CC-HR)covers the entire process from refining liquid steel to manufacturing semi-finished steel *** batch planning and scheduling are connected to the production contract plan at the upper level and the production process contro at the lower level,which is the key to achieving eficient and full process steel *** planning determines the location of the slabs to be produced in the converter,ladle,continuous casting machine,and hot roling mill by combining production orders,process standards,and production *** scheduling,guided by batch planning,combines production performance indicators,process constraints,etc..to determine the equipment selection and start-stop times of speciic production units at each *** synergy of the two aims to optimize production profitability,energy consumption,efficiency,etc.,through rational decisions,ensuring the efficiency and flexibility of the steel production ***,due to the traditional"divide and conguer"management mode and the influence of many uncertain factors,it is dificult to ensure the flexible balance between the demand and capacity,as well as a reasonable matching of logistics and resources among the production processes that operate *** the uncertain environment and the integration of SM-CC-HR,this paper summarizes the research status of previous scholars from three aspects:mathematical modeling,model optimization,and algorithm optimization based on the Lagrangian *** discusses the research status of batch planning and scheduling methods for SM-CC HR production based on the Lagrangian relaxation framework,analyzes the problems existing in current research,and points out the main research directions and important research contents in the future,in order to promote the research and application of batch planning and scheduling problems for SM-CC-HR under uncertain

关键词： steelmaking-continuous castinghot rolling batch planning production scheduling uncertain Lagrangian relaxation

Differential Private Discrete Noise Adding Mechanism: Conditions, Properties and Optimization

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arXiv 2022年

作者： Qin, Shuying He, Jianping Fang, Chongrong Lam, James The Dept. of Automation Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The Dept. of Mechanical Engineering The University of Hong Kong Pokfulam Road Hong Kong

Differential privacy is a standard framework to quantify the privacy loss in the data anonymization process. To preserve differential privacy, a random noise adding mechanism is widely adopted, where the trade-off between data privacy level and data utility is of great concern. The privacy and utility properties for the continuous noise adding mechanism have been well studied. However, the related works are insufficient for the discrete random mechanism on discretely distributed data, e.g., traffic data, health records. This paper focuses on the discrete random noise adding mechanisms. We study the basic differential privacy conditions and properties for the general discrete random mechanisms, as well as the trade-off between data privacy and data utility. Specifically, we derive a sufficient and necessary condition for discrete ∊-differential privacy and a sufficient condition for discrete (∊, δ)-differential privacy, with the numerical estimation of differential privacy parameters. These conditions can be applied to analyze the differential privacy properties for the discrete noise adding mechanisms with various kinds of noises. Then, with the differential privacy guarantees, we propose an optimal discrete ∊-differential private noise adding mechanism under the utility-maximization framework, where the utility is characterized by the similarity of the statistical properties between the mechanism's input and output. For this setup, we find that the class of the discrete noise probability distributions in the optimal mechanism is Staircase-shaped. Copyright © 2022, The Authors. All rights reserved.

关键词： Probability distributions

Neural-LAFC: A Neural Learning Adaptive Flight controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels