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arXiv 2020年

作者： Chen, Zexi Guo, Jiaxin Xu, Xuecheng Wang, Yunkai Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China

Utilizing the trained model under different conditions without data annotation is attractive for robot applications. Towards this goal, one class of methods is to translate the image style from another environment to the one on which models are trained. In this paper, we propose a weakly-paired setting for the style translation, where the content in the two images is aligned with errors in poses. These images could be acquired by different sensors in different conditions that share an overlapping region, e.g. with LiDAR or stereo cameras, from sunny days or foggy nights. We consider this setting to be more practical with: (i) easier labeling than the paired data;(ii) better interpretability and detail retrieval than the unpaired data. To translate across such images, we propose PREGAN to train a style translator by intentionally transforming the two images with a random pose, and to estimate the given random pose by differentiable non-trainable pose estimator given that the more aligned in style, the better the estimated result is. Such adversarial training enforces the network to learn the style translation, avoiding being entangled with other variations. Finally, PREGAN is validated on both simulated and real-world collected data to show the effectiveness. Results on down-stream tasks, classification, road segmentation, object detection, and feature matching show its potential for real applications. Code is available here. Copyright © 2020, The Authors. All rights reserved.

关键词： Stereo image processing

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Radar-on-Lidar: metric radar localization on prior lidar maps

Radar-on-Lidar: metric radar localization on prior lidar map...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huan Yin Yue Wang Li Tang Rong Xiong State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

Radar and lidar, provided by two different range sensors, each has pros and cons of various perception tasks on mobile robots or autonomous driving. In this paper, a Monte Carlo system is used to localize the robot with a rotating radar sensor on 2D lidar maps. We first train a conditional generative adversarial network to transfer raw radar data to lidar data, and achieve reliable radar points from generator. Then an efficient radar odometry is included in the Monte Carlo system. Combining the initial guess from odometry, a measurement model is proposed to match the radar data and prior lidar maps for final 2D positioning. We demonstrate the effectiveness of the proposed localization framework on the public multisession dataset. The experimental results show that our system can achieve high accuracy for long-term localization in outdoor scenes.

关键词： Laser radar Radar Sensors Radar imaging Robots Three-dimensional displays Two dimensional displays

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Fabrication of a Pressure Sensor Using 3d Printed Light-Cured Piezoelectric Composites

SSRN

引用

SSRN 2023年

作者： Wang, Li Ma, Yong Wang, Ke Ma, Yao Lu, Bingheng Niu, Lanjie Li, Xiangyang Micro and Nanotechnology Research Center State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Shaanxi Xi'An710049 China Xi'an Institute of Electromechanical Information Technology Xi'An710065 China Science and Technology on Electromechanical Dynamic Control Laboratory China Dongguan University of Technology China

A 0-3 piezoelectric composite material composed of piezoelectric ceramic particles and polymers combines the performance advantages of both components and has broad prospects for applications in piezoelectric pressure sensors, and 3D printing technology provides a good solution for fabricating complex structures of piezoelectric pressure sensors. However, the current research on stereolithography 3D printing for fabricating piezoelectric appliances focuses on the printing of photosensitive piezoelectric composite slurry, and the piezoelectric output of piezoelectric composites prepared with slurry is low due to the low solid content of the slurry, and an inability to stably store the slurry for a prolonged duration. To improve the piezoelectric output performance, this study investigated the material system and structural design of stereolithography 3D printing of piezoelectric composites based on the dispersion stability of the piezoelectric ceramic paste. The results revealed that 72 wt% paste prepared with oleic acid-grafted and modified piezoelectric ceramic particles has good stability, and the piezoelectric voltage constant of the piezoelectric composites fabricated with paste was 220.2 × 10-3Vm‧N-1, and the piezoelectric sensitivity of the piezoelectric composite after topology optimization could reach 30 mV·kPa-1. A conformal pressure sensor prepared using photocuring 3D printing technology can effectively detect the compressive stress of curved surfaces. © 2023, The Authors. All rights reserved.

关键词： Pressure sensors

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Distributed Adaptive Cooperative control for a Class of Nonlinear Multi-Agent systems via Fully Event-triggered Mechanism

Distributed Adaptive Cooperative Control for a Class of Nonl...

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Annual Conference of industrial Electronics Society

作者： Ming Xiao Zhitao Liu Hongye Su Weihua Xu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

In this paper, the distributed cooperative control for a class of nonlinear multi-agent systems connected by undirected graph is investigated. The dynamic of each agent is first order with unknown mismatched parameters and external disturbances. To reduce the communication burden between each agent and decrease the update frequency of the controllers, the fixed threshold event-triggered mechanisms are considered during the states's broadcasting and the control signals. Based on the adaptive method, the event-based cooperative control protocol is constructed. The asymptotically consensus tracking of all agents are guaranteed and the signals in the closed-loop system are bounded, meanwhile the Zeno behavior is excluded. Simulation results of four agents show the effectiveness and performance of the proposed method.

关键词： Broadcasting Multi-agent systems Protocols Stability analysis Nonlinear dynamical systems Measurement errors Lyapunov methods

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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Multi-Objective Optimization of the Wireless Power Transfer System for Electric Vehicles

Multi-Objective Optimization of the Wireless Power Transfer ...

引用

IEEE Wireless Power Transfer Conference (WPTC)

作者： Ze Zhou Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728142388

ISBN: (纸本)9781728142395

Wireless power transfer (WPT) technology is an effective charging method for electric vehicles. However, when the output power reaches a certain grade, the efficiency decreases with an increase in the output power. Based on this problem, we establish the loss power model of the WPT system, and analyze the efficiency of the WPT system in detail, as well as proposes a multi-objective optimization method to find an optimal control target between the output power and efficiency. Finally, simulation results illustrate that the output power is 10.4 kW and the efficiency is 92.97 % when the system is in the optimal solution state.

关键词： Power generation Simulation Inverters Wireless power transfer Mathematical model MOSFET Immune system

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Efficient Planar Pose Estimation via UWB Measurements

Efficient Planar Pose Estimation via UWB Measurements

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haodong Jiang Wentao Wang Yuan Shen Xinghan Li Xiaoqiang Ren Biqiang Mu Junfeng Wu Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Data Science the Chinese University of HongKong Shenzhen P. R. China College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou P. R. China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing P. R. China School of Mechatronic Engineering and Automation Shanghai University Shanghai P. R. China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing P. R. China

state estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solution. The primary purpose of this work is to investigate planar pose estimation using only UWB range measurements. We prove the excellent property of a two-step scheme, which says we can refine a consistent estimator to be asymptotically efficient by one step of Gauss-Newton iteration. Grounded on this result, we design the GN-ULS estimator, which reduces the computation time significantly compared to previous methods and presents the possibility of using only UWB for real-time state estimation.

关键词：

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A Closed-Loop control Strategy of Maximum Efficiency Point Tracking for Wireless Power Charging System

A Closed-Loop Control Strategy of Maximum Efficiency Point T...

引用

IEEE Wireless Power Transfer Conference (WPTC)

作者： Jia Liu Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9781728142388

ISBN: (纸本)9781728142395

In recent decades, the wireless power transfer (WP-T) has drawn increasing attention of researchers, and the transfer efficiency is one of the most concern aspect. In this paper, a closed-loop control strategy of maximum efficiency point (MEP) tracking is proposed. During the wireless power charging process, the transfer efficiency decreases according to the various load condition and mutual inductor. With the analysis of the optimal load condition and the real-time estimation of mutual inductor, the impedance matching for MEP tracking can be achieved. The buck converter is added to obtain the optimal load condition and the boost converter is inserted to achieve the constant output voltage. By the simulation results, the performance of the closed-loop MEP tracking control strategy has been verified.

关键词： Inductors Resistors Buck converters Voltage control Inductive charging Transmitters Receivers

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Deep Reinforcement Learning Based Optimal Infinite-Horizon control of Probabilistic Boolean control Networks

arXiv

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arXiv 2023年

作者： Ni, Jingjie Li, Fangfei Wu, Zheng-Guang The School of Mathematics East China University of Science and Technology Shanghai200237 China The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China The Institute of Cyber-Systems & Control Zhejiang University Zhejiang Hangzhou310027 China

In this paper, a deep reinforcement learning based method is proposed to obtain optimal policies for optimal infinite-horizon control of probabilistic Boolean control networks (PBCNs). Compared with the existing literatures, the proposed method is model-free, namely, the system model and the initial states needn’t to be known. Meanwhile, it is suitable for large-scale PBCNs. First, we establish the connection between deep reinforcement learning and optimal infinite-horizon control, and structure the problem into the framework of the Markov decision process. Then, PBCNs are defined as large-scale or small-scale, depending on whether the memory of the action-values exceeds the RAM of the computer. Based on the newly introduced definition, Q-learning (QL) and double deep Q-network (DDQN) are applied to the optimal infinite-horizon control of small-scale and large-scale PBCNs, respectively. Meanwhile, the optimal state feedback controllers are designed. Finally, two examples are presented, which are a small-scale PBCN with 3 nodes, and a large-scale one with 28 nodes. To verify the convergence of QL and DDQN, the optimal control policy and the optimal action-values, which are obtained from both the algorithms, are compared with the ones based on a model-based method named policy iteration. Meanwhile, the performance of QL is compared with DDQN in the small-scale PBCN. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Data-based Stabilization of Unknown Discrete-time 2-D Roesser systems

Data-based Stabilization of Unknown Discrete-time 2-D Roesse...

引用

International Conference on Machine Learning and cybernetics (ICMLC)

作者： Runmin Yang Rongni Yang Renjie Ma Yanzheng Zhu Peng Shi School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China School of Electrical and Mechanical Engineering University of Adelaide Adelaide SA Australia

ISBN: (数字)9798331528041

ISBN: (纸本)9798331528058

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

关键词： Sufficient conditions state feedback Two-dimensional displays Transforms Machine learning Stability analysis Data models Numerical models Closed loop systems Numerical stability

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