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IEEE International Conference on Robotics and Biomimetics

作者： Jixue Mo Changqing Gao Hao Fang Qingkai Yang Department of Strategic and Advanced Interdisciplinary Research Peng Cheng Laboratory Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot’s hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment.

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SDN routing optimization based on improved Reinforcement learning 2020

SDN routing optimization based on improved Reinforcement lea...

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Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies

作者： Xiaoye Lu Junyan Chen Liaochuo Lu Xuefeng Huang Xiantao Lu Guangxi Key Laboratory of cloud computing and complex systems Guilin University of Electronic Technology China Guilin

ISBN: (纸本)9781450387828

In recent years, the application of new network architecture SDN combined with reinforcement learning in the field of artificial intelligence is more and more extensive, considering the diversity and complexity of traffic transmission. This paper proposes a DDPG-EREP(Enhanced and renewable experience pool) algorithm that dynamically plans the experience pool capacity and sampling size according to the current iteration number, and can update the experience in time, and applies it to SDN routing optimization. In addition, good results have been achieved through experiments, including better training speed and better routing optimization of SDN.

关键词： Reinforcement Learning Routing optimization DDPG SDN

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An interpretability analysis of travel decision learning in cyber-physical-social-systems 1

An interpretability analysis of travel decision learning in ...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Miao Ye, Peijun Liu, Xudong Liu, Sheng Xiong, Gang Zhang, Liguo Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

ISBN: (纸本)9781665433372

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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Fast calibration of agent-based model using mean-field approach 1

Fast calibration of agent-based model using mean-field appro...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Lu, Wanze Xiong, Gang Liu, Xudong Liu, Sheng Ye, Peijun Zhang, Liguo Beijing University of Technology Faculty of Information and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

Calibration of simulation system is an important step to establish a reliable simulation system. In this paper, based on the existing mean field calibration theory, a new fast calibration method for complex urban traffic system based on mean field method is discussed by establishing the relationship between the macroscopic observation quantity and the proxy microscopic parameters. This method makes use of the machine learning method, and reduces the dimension of the state vector in the discrete time period, so that the dimension of the macroscopic state transition matrix is lower, and then reduces the computational complexity of the system calibration. Finally, the calibration results of the simulation system were verified by SUMO traffic simulation software. © 2021 IEEE.

关键词： Calibration

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Dynamic Resource Scheduling Based on Improved Genetic Algorithm

Dynamic Resource Scheduling Based on Improved Genetic Algori...

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第40届中国控制会议

作者： Gui Yuanyuan School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at the problem of how to realize the reasonable distribution of goods and the resource scheduling of route planning under dynamic conditions, a phased refresh method is proposed to deal with the requirements in sections. At the same time, the clustering method is introduced to generate the initial population. And the cross and mutation rate is determined by a step-by-step reduction method, which is used to solve the problem of the traditional genetic algorithm falling into the local optimum caused by the uneven distribution of searchable solutions. Finally, the effectiveness of the improved method is verified by simulation experiments.

关键词： resource scheduling phased refresh improved genetic algorithm

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Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws

arXiv

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arXiv 2024年

作者： Zhang, Jingdong Zhu, Qunxi Lin, Wei School of Mathematical Sciences SCMS SCAM Fudan University Shanghai200433 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Fudan University Shanghai200032 China

Accurately finding and predicting dynamics based on the observational data with noise perturbations is of paramount significance but still a major challenge presently. Here, for the Hamiltonian mechanics, we propose the Hamiltonian Neural Koopman Operator (HNKO), integrating the knowledge of mathematical physics in learning the Koopman operator, and making it automatically sustain and even discover the conservation laws. We demonstrate the outperformance of the HNKO and its extension using a number of representative physical systems even with hundreds or thousands of freedoms. Our results suggest that feeding the prior knowledge of the underlying system and the mathematical theory appropriately to the learning framework can reinforce the capability of machine learning in solving physical problems. © 2024, CC BY.

关键词： Hamiltonians

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Delay-Dependent Stability Analysis of Multi-Area Load Frequency Control systems with Multiple Renewable Energy Structures

Delay-Dependent Stability Analysis of Multi-Area Load Freque...

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Chinese Control Conference (CCC)

作者： Qian-Long Pan Li Jin Yong He Zhou-Zhou Liu School of Automation China University of Geosciences Wuhan P.R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P.R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P.R. China

This paper investigates the delay-dependent stability of time-delayed load frequency control (LFC) systems with multiple energy structures based on Lyapunov theory and linear matrix inequality (LMI) technology. Firstly, a multi-area delayed LFC model considering multiple renewable energy structures is established. Then, in order to improve the computation efficiency of stability analysis of large scale LFC systems, a new reconstruction technique for system model is proposed. Next, the improved delay-dependent stability criteria are established based on reconstructed model by using the Lyapunov stability theory. Finally, case studies are based on two-area LFC systems. Comparing with the criterion based on the original model without reconstruction, the calculation efficiency of proposed stability criteria has been greatly improved with the cost of small accuracy, and the calculation accuracy is better than the previous methods.

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Forecasting Approach in Fuzzy Time Series Based on Information Granules

Forecasting Approach in Fuzzy Time Series Based on Informati...

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第40届中国控制会议

作者： Kaixin Zhao Yaping Dai Ye Ji Jiayi Sun School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at a large number of ambiguous,imprecise and incomplete data in the real world,fuzzy time series has come into being and developed into an effective forecasting *** the process of modeling and forecasting of fuzzy time series,the prediction performance of fuzzy time series can be effectively improved by partitioning the universe of discourse into different *** this paper,a forecasting approach for fuzzy time series,which introduces the granularity mechanism into interval division and employs differential data for incremental forecasting,is proposed to solve the problem of time series forecasting with high forecasting *** the proposed approach,in order to describe the fuzzy logic relationship and fuzzy trend of historical data,we first do differential processing on the historical ***,Fuzzy C-means(FCM) clustering algorithm is used to generate several partition intervals *** the sequel,we use the principle of justifiable granularity to constantly adjust the width of all the intervals,so that these information granules associated with corresponding intervals become the most"informative" information ***,the boundary of information granules is used as the basis of interval division to complete the forecasting *** illustrative example is provided to demonstrate the essence of the proposed *** comparative experiment with other representative approaches shows that the proposed approach can significantly improve the prediction accuracy of time series.

关键词： Fuzzy Time Series Information Granules Unequal-sized Intervals Forecasting

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Multimodal Image Matching based on Frequency-domain Information of Local Energy Response

arXiv

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arXiv 2025年

作者： Yang, Meng Chen, Jun Gong, Wenping Wei, Longsheng Tian, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China Electronic Information School Wuhan University Wuhan430072 China

Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a method based on Frequency-domain Information of Local Energy Response called FILER. The core of FILER is the local energy response model based on frequency-domain information, which can overcome the effect of nonlinear intensity differences. To improve the robustness to local nonlinear geometric distortions and noises, we design a new edge structure enhanced feature detector and convolutional feature weighted descriptor, respectively. In addition, FILER overcomes the sensitivity of the frequency-domain information to the rotation angle and achieves rotation invariance. Extensive experiments multimodal image pairs show that FILER outperforms other state-of-the-art algorithms and has good robustness and *** Codes 68U10 (Primary), 68T45, 68Wxx (Secondary) Copyright © 2025, The Authors. All rights reserved.

关键词： Mathematical transformations

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Path Tracking Control of Tracked Paver Based on Improved Pure Pursuit Algorithm

Path Tracking Control of Tracked Paver Based on Improved Pur...

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第40届中国控制会议

作者： Shuai Wang Shanshan Fu Bin Li Shoukun Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

This paper investigates the high-precision path tracking control of tracked paver combined with global satellite navigation *** the paver is performing paving operations,it requires high path tracking accuracy and good vehicle ***,considering the influence of road curvature on path tracking accuracy and vehicle stability,and the situation that the vehicle can not move quickly to the expectation path when the lateral position of the vehicle deviates from the expectation path,this paper proposes a lateral path tracking control method based on improved Pure Pursuit *** control method is verified through *** experimental results show that the maximum lateral tracking error of the improved algorithm is 0.04 m,which is 55.56% lower than that of the original algorithm,and the average lateral tracking error is 0.02 m,which is60% lower than that of the original *** purpose of high-precision path tracking of the paver is realized.

关键词： Tracked paver Path tracking Road curvature Pure Pursuit algorithm

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