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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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Preventive control Methods for Power systems Based on Improved Deep Reinforcement Learning 6

Preventive Control Methods for Power Systems Based on Improv...

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6th International Conference on Power and Energy Technology, ICPET 2024

作者： Zhang, Jie Zhu, Yihua Liang, Zhuohang Zhang, Qingqing Ma, Qinfeng Liu, Mingshun An, Su Dai, Jiang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd Guiyang China

ISBN: (纸本)9798350375855

Convergence speed, accuracy, generalization and decision transparency are very important indices for transient stability preventive control generation methods based on AI. This paper proposes a transient stability preventive control generation method based on graph deep reinforcement learning and its interpretation method using mutual information optimization. Firstly, a transient stability preventive control generation model is built based on the framework of deep reinforcement learning algorithm. The grid domain buses are mapped to the graph domain nodes and the grid graph data samples are generated. The graph convolutional neural network via initial residual and identity mapping (GCNII) is used to build the action network and the evaluation network. Secondly, based on the GCNII network, a transient stability assessment model is built and pre-trained, and graph data samples containing varies of topological structures and power flow states are applied to train the model. Then the interpretation method based on mutual information optimization is used to analyze the decision-making basis of the transient stability assessment model. The dominant factor affecting the transient instability of power system is extracted and its contribution degree is quantified, and the abduction analysis of transient stability is realized. Finally, the pre-trained transient stability assessment model is embedded in the deep reinforcement learning framework as a guide, and the power flow adjustment method is used to preferentially correct the weak factors and their influencing factors so that the transient stability prevention control strategies are obtained. The feasibility and effectiveness of the proposed method are verified in the IEEE-39 node test system. © 2024 IEEE.

关键词： Transient stability

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Parametric Approach to Missile Formation control

Parametric Approach to Missile Formation Control

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Yutao Zhuang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing

Under the condition of strong connectivity, the formation keeping problem of missile formation based on high-order fully actuated system is studied. The time-varying controller of the system is designed for the formation tracking of missile formation and disturbance suppression by upgrading the first-order model to the second-order model and using the parametric approach. The numerical simulation experiments of the system are completed with the introduction of bounded random disturbances. The motion trajectory, position tracking error, velocity tracking error and control force output of the missile formation are analyzed, and the final steady-state error is basically stabilized within 0.1, and the control force is controlled at about 2000 N during the formation holding phase.

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High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain

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Chinese Journal of Aeronautics 2021年第5期34卷 652-665页

作者： Kang XU Shoukun WANG Junzheng WANG Xiuwen WANG Zhihua CHEN Jinge SI School of Automation Beijing Institute of Technology.Beijing 100081China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China Key Laboratory Ministry of Industry and Information Technology Beijing Institute of TechnologyBeijing 100081China

There is a strong demand for Planetary Exploration Mobile robots(PEMRs)that have the capability of the traversability,stability,efficiency and high load while tackling the specialized tasks on planet *** this paper,an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is ***,the hybrid control framework,which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion,is also *** on this framework,robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator(GG).Additionally,by using Whole-Body control(WBC)of framework,robot has the capability of flexibly accommodating the uneven terrain by Attitude control(AC)kinematically adjusting the length of legs like an active suspension system,and by Force/torque Balance control(FBC)equally distributing the Ground Reaction Force(GRF)to maintain a stable *** simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog ***,to smoothly demonstrate the performance of robot transporting heavy loads,the experiment of carrying 3-person load of about 240 kg is deployed.

关键词： Attitude control Gait generation High-adaption locomotion Obstacle avoidance Planetary exploration robot

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An intelligent Ranking Evaluation Method of Simulation Models Based on Graph Neural Network 15th

An Intelligent Ranking Evaluation Method of Simulation Model...

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15th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2023

作者： Yang, Fan Ma, Ping Zhang, Jianchao Cheng, Huichuan Li, Wei Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Modeling and Simulation Harbin150080 China Chinese Aeroengine Research Institute Beijing101304 China

ISBN: (纸本)9783031575228

To validate the alternative simulation models and select the most credible one when the models have multivariate and correlated outputs, an intelligent ranking evaluation method of simulation models based on Graph Neural Network (GNN) is proposed. The process of ranking evaluation is divided into three parts: graph structure conversion for evaluation data, feature extraction based on Graph Representation Learning (GRL) and ranking evaluation based on feature distance. A graph structure modeling method is presented to provide the pre-define graph structure for further GRL primarily. Next the interdependencies and dynamic evolutionary patterns among variables are captured by GNN so that the graph representations of evaluation data can be obtained. Then ranking evaluation is achieved by similarity measurement of the graph representations. In the end, the effectiveness of the proposed method on feature extraction of evaluation data and simulation models ranking is illustrated through an application example on a prediction model for aerodynamic parameters of a certain flight vehicle. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Feature extraction

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Optimization Strategy for Virtual Energy Storage of Electric Vehicles to Participate in Multiple Ancillary Services 5

Optimization Strategy for Virtual Energy Storage of Electric...

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5th International Conference on Clean Energy and Electric Power Engineering, ICCEPE 2024

作者： Guo, Qi Gu, Haohan Zhao, Yifei Tu, Liang Chen, Qifang Cai, Haiqing Chen, Wei Chen, Zhihao Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China School of Electrical Engineering Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798350390315

When EVs participate in multiple ancillary services of the power grid, due to the lack of a unified management scheduling plan, various ancillary service demands compete for limited energy storage resources. This would lead to conflicts when the virtual energy storage of EV participates in the regulation of multiple ancillary services. In order to solve the above problems, a reasonable and feasible optimization strategy for virtual energy storage of EVs is formulated to alleviate the conflict problems of ancillary services. The validity of the proposed method is verified by simulation cases. © 2024 IEEE.

关键词： control strategies electric vehicles multiple auxiliary services

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Multi-Objective Reactive Power Compensation Optimization for Power Grid with Large Scale Offshore Wind Farms 7

Multi-Objective Reactive Power Compensation Optimization for...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Zhou, Heng Tan, Zukuang Liu, Yutian Control of Ministry of Education of Shandong University Key Laboratory of Power System Intelligent Dispatch Jinan250061 China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

Offshore wind power has a wide developing space in the future because of the increasing demand for green energy. In this paper, a multi-objective reactive power compensation optimization method of power grid integrated with large scale offshore wind farms is presented to optimize the capacity of reactive power compensation. The optimization objectives are considered including voltage deviation, voltage stability, active power loss and total reactive power compensation. Fuzzy optimization model is introduced based on fuzzy evaluation function and fuzzy analytic hierarchy process. Simulation results of Shandong power grid of China demonstrate that the proposed reactive power compensation optimization method can improve the voltage stability and economic effectiveness. © 2022 IEEE.

关键词： Offshore wind farms

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Parallel Learning:Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 603-631页

作者： Qinghai Miao Yisheng Lv Min Huang Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Artificial Intelligence Anhui UniversityHefei 266114China Qingdao Academy of Intelligent Industries Qingdao 230031China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine *** summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel ***,an extended parallel learning framework is proposed to cover main domains including computer vision,natural language processing,robotics,and autonomous ***,a multi-dimensional taxonomy is designed to organize the literature in a hierarchical ***,the related virtual-toreal works are analyzed and compared according to the three principles of parallel learning known as description,prediction,and prescription,which cover the methods for constructing virtual worlds,generating labeled data,domain transferring,model training and testing,as well as optimizing the strategies to guide the task-oriented data generator for better learning *** issues remained in virtual-to-real are ***,the future research directions from the viewpoint of parallel learning are suggested.

关键词： Machine learning parallel learning parallel systems sim-to-real syn-to-real virtual-to-real

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LI-DPS: A Long Sequence Dual Prediction Scheme Based on Informer for Efficient High-Frequency Data Transmission 50

LI-DPS: A Long Sequence Dual Prediction Scheme Based on Info...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wu, Yu Yang, Bo Zhu, Dafeng Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665464543

High-frequency time-series data such as vibration signals will consume a lot of communication resources and require very high network bandwidth. Reducing the amount of data transmission while ensuring its availability is particularly important and challenging in high-frequency scenarios. Dual prediction scheme (DPS) can significantly reduce the amount of data transmission while ensuring data accuracy. However, traditional DPS cannot be applied to high-frequency scenarios due to the limitation of the mechanism design and model inference speed. We propose a novel long sequence DPS to efficiently reduce the volume of high-frequency data transmission in real time. To overcome the accuracy degradation due to gradient vanishing in long sequence prediction, we also propose an attention-based prediction model. Furthermore, we propose Informer to reduce the model’s computational complexity and enable fast inference and deployment on resource-constrained edge gateways. Experiments based on the real-world dataset show that the proposed scheme can efficiently cope with high-frequency data, reduce its transmission volume, and ensure data accuracy. © 2024 IEEE.

关键词： Prediction models

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Color liquid crystal grating based color holographic 3D display system with large viewing angle

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Light(Science & Applications) 2024年第1期13卷 103-112页

作者： Di Wang Yi-Long Li Fan Chu Nan-Nan Li Zhao-Song Li Sin-Doo Lee Zhong-Quan Nie Chao Liu Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Display Technology Research Center Seoul National UniversityGwanak-ro 1Gwanak-guSeoul 08826Republic of Korea Key Lab of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China

Holographic 3D display is highly desirable for numerous applications ranging from medical treatments to military ***,it is challenging to simultaneously achieve large viewing angle and high-fidelity color reconstruction due to the intractable constraints of existing ***,we conceptually propose and experimentally demonstrate a simple and feasible pathway of using a well-designed color liquid crystal grating to overcome the inevitable chromatic aberration and enlarge the holographic viewing angle,thus enabling large-viewing-angle and color holographic 3D *** use of color liquid crystal grating allows performing secondary diffraction modulation on red,green and blue reproduced images simultaneously and extending the viewing angle in the holographic 3D display *** principle,a chromatic aberration-free hologram generation mechanism in combination with the color liquid crystal grating is proposed to pave the way for on such a superior holographic 3D *** proposed system shows a color viewing angle of~50.12°,which is about 7 times that of the traditional system with a single spatial light *** work presents a paradigm for achieving desirable holographic 3D display,and is expected to provide a new way for the wide application of holographic display.

关键词： holographic angle crystal

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