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2021 China automation Congress, CAC 2021

作者： Qian, Kun Cai, Yeyun Xu, Kun Deng, Fang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781665426473

Heat dissipation is extremely important for electronic component such as CPU or GPU of the computer. Now most researchers only design optimal heat sink for CPU for better heat dissipation, while few of them consider waste heat recycling of CPU. The CPU can be used as the heat source, while the original system has fan and heat sink as the cooling system. Thus, the original CPU working condition is very suitable for thermoelectric power generation and will bring great benefit to system itself. However, adding thermoelectric generator will increase the temperature of CPU, which will decrease the performance of the computer. It is necessary to reduce the hot side temperature while generating energy as much as possible. To achieve this, this paper designed a kind of intelligent waste heat generation system based on thermoelectric power generator. Three different shape heat sinks are designed, contrasted, and tested. By building experimental platform and establishing simulation model, the power of thermoelectric power generation and temperature change of the three heat sink structures are compared. The fin shaped heat sink is considered has the best output performance while keeping the hot side temperature within the acceptance range. The maximum output power is 10.67mW, and the maximum hot side temperature is 72◦C during the experiment. © 2021 IEEE

关键词： Waste heat

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Multiple–Model UKF/CKF State Estimation for Nonlinear systems

Multiple–Model UKF/CKF State Estimation for Nonlinear Syste...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Shi, Xiaodi Yan, Liping Xia, Yuanqing Xiao, Bo Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811581540

In most control systems, modeling error and noise interference will always lead to the performance degradation and divergence of the UKF or the CKF. To settle a matter caused by model uncertainties, a new UKF/CKF frame combined with multiple model method is presented in this paper. Through probabilistic multiple model design method, this paper approximates the posterior densities by a finite number of probabilistically weighted points and uses these points to display the entire state space. Simulation results and comparison analysis demonstrate that the multiple-model UKF(MMUKF) and the multiple-model CKF(MMCKF) have higher precision and stronger robustness than the traditional UKF and CKF in case of model uncertainties. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Uncertainty analysis

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Differentially Private Recursive Least Squares Estimation for ARX systems with Multi-Participants

arXiv

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arXiv 2025年

作者： Tan, Jianwei Wang, Jimin Zhang, Ji-Feng Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China School of Automation and Electrical Engineering Zhongyuan University of Technology Zheng Zhou450007 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

This paper proposes a differentially private recursive least squares algorithm to estimate the parameter of autoregressive systems with exogenous inputs and multi-participants (MP-ARX systems) and protect each participant’s sensitive information from potential attackers. We first give a rigorous differential privacy analysis of the algorithm, and establish the quantitative relationship between the added noises and the privacy-preserving level when the system is asymptotically stable. The asymptotic stability of the system is necessary for ensuring the differential privacy of the algorithm. We then give an estimation error analysis of the algorithm under the general and possible weakest excitation condition without requiring the boundedness, independence and stationarity on the regression vectors. Particularly, when there is no regression term in the system output and the differential privacy only on the system output is considered, Ε-differential privacy and almost sure convergence of the algorithm can be established simultaneously. To minimize the estimation error of the algorithm with Ε-differential privacy, the existence of the noise intensity is proved. Finally, two examples are given to show the efficiency of the algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Differential privacy

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A* Algorithm

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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Chinese control Conference (CCC)

作者： Zhi Liu Lin Zhang Shoukun Wang Tianwei Niu Yongkang Xu Jin Cao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A* algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A* combined with reverse path and dynamic window method (DWA-IMP-A*) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A* algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles.

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An Automatic Hand Rehabilitation Assessment System: Implementation and Experiments 12

An Automatic Hand Rehabilitation Assessment System: Implemen...

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12th International Conference on CYBER Technology in automation, control, and Intelligent systems, CYBER 2022

作者： Wang, Yifan Cheng, Long Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100190 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The lack of rehabilitation therapists and the increase of disabled individuals have reduced the opportunities for patients to receive well rehabilitation assessment. Towards solving this challenge, establishing a therapist-assistance assessment system to reduce the medical resource consumption is demanding. This paper proposes an automatic hand rehabilitation assessment system based on the Leap Motion vision sensor and a self-designed hand strength measurement device. The assessment algorithm requires the patients to complete every motion given in Fugl-Meyer assessment scale (FMA), and automatically scores the completion level of each motion via recognizing different hand gestures and hand grasping strength. As illustrated by the experiments on ten volunteers, the proposed assessment system can obtain the reliable scores which are consistent with the ones manually obtained via FMA. © 2022 IEEE.

关键词： Patient rehabilitation

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A 3D Virtual Try-On Method with Global-Local Alignment and Diffusion Model

A 3D Virtual Try-On Method with Global-Local Alignment and D...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shougan Pan Zhengwentai Sun Chenxing Wang Junkai Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China The Hong Kong Polytechnic University Institute of Automation Chinese Academy of Sciences

3D virtual try-on has recently received more attention due to its great practical and commercial value. However, there remains the problems that the garment cannot accurately correspond to a human body by geometric transformation and abnormal textures may be produced in the synthesis result. To address these issues, a 3D virtual try-on method with global-local alignment and diffusion model is proposed. The global-local alignment module is designed for more accurate garment warping, combined with the guidance of an "after-try-on" semantic map alignment. Then, a diffusion model is introduced to design a try-on synthesizer that can not only avoid producing abnormal textures but also enhance the quality of textures produced in edge regions. Experiments on existing datasets show that our method outperforms the state-of-the-art methods. Code is available at https://***/Breaveh/VTON-GD.

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EGCN: Ensemble Graph Convolutional Network for Neural Architecture Performance Prediction

EGCN: Ensemble Graph Convolutional Network for Neural Archit...

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2021 International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2021

作者： Liu, Xin DIng, Zixiang Li, Nannan Chen, Yaran Zhao, Dongbin Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China

ISBN: (纸本)9781665402453

Neural Architecture Search (NAS) is proposed to automatically search novel neural networks. Currently, one typical problem of NAS is that its computation requirements are too high to stand for most researchers. In fact, it consumes a lot of resources to train subnetworks for architecture search. If the performance of each subnetwork can be predicted accurately without training, the computational burden will be alleviated. Graph Convolutional Network (GCN) is proven to have powerful capabilities for topological information perception and extraction. It is suitable to use GCN for predicting neural architecture performance which is related to its *** this paper, we treat GCN as the performance predictor with two improvements. First, a novel neural architecture data processing method named DATAPRO2 is designed to improve GCN's performance. Then, we propose EGCN, a model-based performance predictor which employs ensemble technique on GCN with DATAPRO2 to alleviate the overfitting issue caused by the imbalanced dataset for neural architecture performance prediction. Experimental results on CVPR-2021-NAS-TRACK2 dataset show that EGCN contributes to obtaining better predictive performance than vanilla GCN and other popular predictors. © 2021 IEEE.

关键词： Topology

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Application of Hybrid Variable Admittance Force Tracking and Fixed-time Position control for Robot Interaction Tasks

Application of Hybrid Variable Admittance Force Tracking and...

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International Conference on control, Mechatronics and automation (ICCMA)

作者： Hong Zhan Chao Zeng Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Computer Science University of Liverpool Liverpool UK

ISBN: (数字)9798331517519

ISBN: (纸本)9798331517526

This paper applies the proposed hybrid force and position control method to the physical robot system with interaction tasks to further improve our previous study. In the control scheme, the variable stiffness based on proportional integral derivative(PID) admittance control is adopted for interaction force tracking and the radial basis function neural network(RBFNN) based fixed-time control is designed to ensure position tracking. We have performed interaction tasks based on a Baxter robot for drawing on the plane and slope plane with different expected interaction forces and position trajectories. The experiment results indicate that the method performs well in terms of interaction force and trajectory tracking.

关键词： Mechatronics automation Trajectory tracking Force Dynamics Position control Trajectory Robots Admittance control Convergence

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Finite-time coordinated path-following control of leader-following multi-agent systems

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Frontiers of Information Technology & Electronic Engineering 2022年第10期23卷 1511-1521页

作者： Weibin CHEN Yangyang CHEN Ya ZHANG School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China Robot Department Jiangsu Automation Research InstituteLianyungang 222061China

This paper presents applications of the continuous feedback method to achieve path-following and a formation moving along the desired orbits within a finite *** is assumed that the topology for the virtual leader and followers is *** additional condition of the so-called barrier function is designed to make all agents move within a limited area.A novel continuous finite-time path-following control law is first designed based on the barrier function and *** a novel continuous finite-time formation algorithm is designed by regarding the path-following errors as *** settling-time properties of the resulting system are studied in detail and simulations are presented to validate the proposed strategies.

关键词： Finite-time Coordinated path-following Multi-agent systems Barrier function

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