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IEEE International Conference on automation Science and Engineering (CASE)

作者： Qihang Fang Gang Xiong Xiuqin Shang Sheng Liu Bin Hu Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Fault diagnosis is a vital technique to pinpoint the machine malfunctions in manufacturing systems. In recent years, the deep learning techniques greatly improve the fault detection accuracy, but there still remain some problems. If one fault is absent in the training data or the fault signal is disturbed by severe noise interference, the fault classifier may misjudge the health state. This problem limits the reliability of the fault diagnosis in real applications. In this paper, we enhance the fault diagnosis method by using Bayesian Convolutional Neural Network (BCNN). A Shannon entropy-based method is presented to quantify the prediction uncertainty. The BCNN turns the deterministic predictions to probabilistic distributions and enhances the robustness of the fault diagnosis. The uncertainty quantification method helps to indicate the wrong predictions, detect unknown faults, and discover the strong disturbances. Then, a fine-tuning strategy is applied to enhance the model performance further. The potential usability of the proposed method in monitoring the motors of 3D printers is studied. And the experiment is conducted on a motor bearing dataset provided by Case Western Reserve University. The proposed BCNN achieves 99.82% fault classification accuracy over nine health conditions. Its robustness is verified by comparing the testing accuracy with three other methods on the noisy datasets. And the uncertainty quantification method successfully detects the outlier inputs.

关键词： Fault diagnosis Uncertainty Bayes methods Circuit faults Robustness Predictive models Noise measurement

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Resonant beam communications with echo interference elimination

arXiv

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arXiv 2021年

作者： Xiong, Mingliang Liu, Qingwen Wang, Gang Giannakis, Georgios B. Zhang, Sihai Zhu, Jinkang Huang, Chuan College of Electronics and Information Engineering Tongji University Shanghai201804 China State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Key Lab of Wireless-Optical Communications University of Science and Technology of China Hefei Anhui230026 China School of Science and Engineering Chinese University of Hong Kong Shenzhen Guangdong518172 Hong Kong

Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier. Besides, the RBCom system possesses the characteristics of mobility, high signal-to-noise ratio (SNR), and multiplexing. Nevertheless, the channel of the RBCom system is distinct from other light communication technologies due to the echo interference issue. In this paper, we reveal the mechanism of the echo interference and propose the method to eliminate the interference. Moreover, we present an exemplary design based on frequency shifting and optical filtering, along with its mathematic model and performance analysis. The numerical evaluation shows that the channel capacity is greater than 15 bit/s/Hz. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

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An Adaptive RBF Neural Network control Method for a Class of Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 457-462页

作者： Hongjun Yang Jinkun Liu State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation Science and Electrical Engineering Beihang University Beijing 100083 China

This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unknown functions and external disturbances in the nonlinear system are overcome by RBFNN, combined with the single parameter direct adaptive control method. The novel adaptive control method is designed to reduce the amount of computations *** uniform ultimate boundedness of the closed-loop system is guaranteed by the proposed controller. A coupled motor drives(CMD) system, which satisfies the structure of nonlinear system,is taken for simulation to confirm the effectiveness of the *** show that the developed adaptive controller has favorable performance on tracking desired signal and verify the stability of the closed-loop system.

关键词： Index TermsbAdaptive control neural network （NN） nonlin-ear system radial basis function.

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Motion optimization for a robotic fish based on adversarial structured control

Motion optimization for a robotic fish based on adversarial ...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Yan, Shuaizheng Wang, Jian Wu, Zhengxing Yu, Junzhi Tan, Min Institute of Automation CAS State Key Lab Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Dept. Mech. Eng. Sci. BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9781728163215

This paper proposes a task-based control optimization method for the robotic fish. It is essentially an adversarial structured control consisting of a global control module and a local compensation control module. In detail, the global control module emulates an optimized central pattern generator with Evolutionary Strategy, while the local control module produces targeted compensation control signals with Soft Actor-Critic. The linear summation of two control laws works for the final robotic fish control. Considering that the evolutionary computation optimization algorithms generally have the defect of falling into the local optimum, we propose a method of antagonistic training to improve the optimization performance. The effectiveness of the designed controller is validated by simulation on agents in Mujoco. Noticeably, the simulation results demonstrate that the proposed method teaches the agent fish to move to any target point with a low energy consumption, which lays a good foundation for application of reinforcement learning in real robotic fish control. © 2019 IEEE.

关键词： Fish

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Design and yaw control of a two-motor-actuated biomimetic robotic fish

Design and yaw control of a two-motor-actuated biomimetic ro...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Du, Sheng Wu, Zhengxing Yu, Junzhi Institute of Automation CAS State Key Lab Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Dept. Mech. Eng. Sci. BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9781728163215

This paper addresses the design and control of a novel tuna-inspired robotic fish able to realize both fast swimming and high maneuverability. A two-stage transmission mechanism is proposed, aiming at reducing the volume and mass of caudal peduncle. Benefited by it, both volumes and mass of moving parts can be reduced to allow higher swing frequency. At the same time, two joints driven by two motors ensure the flexibility of steering. The robotic fish achieves a maximum speed up to 1.65 body lengths per second (BL/s) and a minimum turning radius less than 0.35 body lengths (BL), based on the open-loop control designed by Central Pattern Generator (CPG) method. Furthermore, a yaw control is proposed to maintain course angle at high swimming speed, and simulation in Automatic Dynamic Analysis of Mechanical systems (ADAMS) software reveals the effectiveness. The results show that the proposed yaw control method can regulate the fluctuation of anterior body to desired range but without compensation of sideways drift. © 2019 IEEE.

关键词： Fish

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3-D motion analysis and implementation of a developed gliding robotic dolphin

3-D motion analysis and implementation of a developed glidin...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Wang, Jian Wu, Zhengxing Liu, Jincun Tan, Min Yu, Junzhi Institute of Automation CAS State Key Lab Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Dept. Mech. Eng. Sci. BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9781728163215

This paper investigates the three-dimensional (3-D) maneuverability of a gliding robotic dolphin through analyzing the horizontal and vertical motions. Concretely, in order to improve the performance in the horizontal plane, the gliding robotic dolphin is developed with a rudder installed on its belly, and the 3-D full-state dynamic model is derived briefly. By setting two typical body and/or caudal fin (BCF)-based and three typical median and/or paired fin (MPF)-based turning patterns, the turning performances are revealed and analyzed. With regard to the vertical plane, a novel finite state machine framework is proposed to realize the vertical downward action. Finally, extensive experiments involving the turning and vertical motions are conducted to illustrate and analyze the 3-D maneuverability, which provides valuable guidance for the real-world applications of the gliding robotic dolphin. © 2019 IEEE.

关键词： Motion analysis

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Adaptive Dynamic Programming Method for Optimal Battery management of Battery Electric Vehicle

Adaptive Dynamic Programming Method for Optimal Battery Mana...

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Data Driven control and Learning systems (DDCLS)

作者： Jiguang Xue Chunsheng Yan Dan Wang Jun Wang Jun Wu Zehua Liao Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd Shenyang China LiaoNing Electric Power Development Stock Co. LTD Shenyang China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

One of the main influencing factors of battery electric vehicle (BEV) application is the high-cost of the battery. We consider to apply the battery of BEV to smart residential environments when the BEV is idle, so that we can lower the utility cost. Therefore, an adaptive dynamic programming (ADP) method is designed to solve the optimal battery management, which avoids the dimension disaster of the complex nonlinear BEV system. First, the operation modes of the battery are analyzed, and the problem statement is carried out. Then, the corresponding self-learning optimization algorithm is developed based on ADP. Finally, numerical results by experiment simulations are used to verify the ADP algorithm.

关键词： Batteries Optimal control Dynamic programming Battery management systems Power grids Discharges (electric) Adaptation models

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Design of a low-cost miniature robot to assist the COVID-19 nasopharyngeal swab sampling

arXiv

引用

arXiv 2020年

作者： Wang, Shuangyi Wang, Kehao Liu, Hongbin Hou, Zengguang The State Key Laboratory of Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University China The School of Biomedical Engineering and Imaging Sciences King's College London United Kingdom

Nasopharyngeal (NP) swab sampling is an effective approach for the diagnosis of coronavirus disease 2019 (COVID-19). Medical staffs carrying out the task of collecting NP specimens are in close contact with the suspected patient, thereby posing a high risk of cross-infection. We propose a low-cost miniature robot that can be easily assembled and remotely controlled. The system includes an active end-effector, a passive positioning arm, and a detachable swab gripper with integrated force sensing capability. The cost of the materials for building this robot is 55 USD and the total weight of the functional part is 0.23kg. The design of the force sensing swab gripper was justified using Finite Element (FE) modeling and the performances of the robot were validated with a simulation phantom and three pig noses. FE analysis indicated a 0.5mm magnitude displacement of the gripper's sensing beam, which meets the ideal detecting range of the optoelectronic sensor. Studies on both the phantom and the pig nose demonstrated the successful operation of the robot during the collection task. The average forces were found to be 0.35N and 0.85N, respectively. It is concluded that the proposed robot is promising and could be further developed to be used in vivo. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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FSD-10: A dataset for competitive sports content analysis

arXiv

引用

arXiv 2020年

作者： Liu, Shenglan Liu, Xiang Huang, Gao Feng, Lin Hu, Lianyu Jiang, Dong Zhang, Aibin Liu, Yang Qiao, Hong Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China Faculty of Tsinghua University of Technology Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep learning, such process has been slow in competitive sports content analysis. To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for finegrained sports content analysis. To this end, we collect 1484 clips from the worldwide figure skating championships in 2017-2018, which consist of 10 different actions in men/ladies programs. Each clip is at a rate of 30 frames per second with resolution 1080 × 720. These clips are then annotated by experts in type, grade of execution, skater info,.etc. To build a baseline for action recognition in figure skating, we evaluate state-of-the-art action recognition methods on FSD-10. Motivated by the idea that domain knowledge is of great concern in sports field, we propose a keyframe based temporal segment network (KTSN) for classification and achieve remarkable performance. Experimental results demonstrate that FSD-10 is an ideal dataset for benchmarking action recognition algorithms, as it requires to accurately extract action motions rather than action poses. We hope FSD-10, which is designed to have a large collection of finegrained actions, can serve as a new challenge to develop more robust and advanced action recognition models. Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

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Micro/nanoliter droplet extraction by controlling acoustic vortex with miniwatt

arXiv

引用

arXiv 2021年

作者： Zhang, Han Yang, Jun Zhou, Yun Zheng, Jianfeng Cheng, Yong Bai, Bichao Zhang, Guoxin Lv, Yisheng CAS Key Laboratory of Noise and Vibration Institute of Acoustics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China The National Center for Nanoscience and Technology Beijing100190 China School of Mechanical Engineering Changzhou University Changzhou213164 China Institute of Mechanics School of Civil Engineering & Mechanics Yanshan University Qinhuangdao066004 China Al-ion Battery Research Center Department of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266580 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Micro/nanoliter droplet is capable of achieving versatile applications with tiny volume and substantial surface energy, which is a big plus over bulk liquid. Yet, the contradiction of elaborate manipulation and enough power is still a challenge. Here, we unleash the potential of our miniwatt aspirators pumping up liquid and creating droplets with the help of acoustic vortex beams, inspired by the power mechanism that spirals are significant for most mollusks that live in water. These droplet aspirators produce very large interface deformations by small radiation pressures with orbit angular momentum from spiral-electrode transducers. The precisely contactless manipulation of physical, chemical and biological objects at micrometric down to nanometric scales, promises tremendous development in fields as diverse as microrobotics, nanoreactors, or nanoassemblies. Copyright © 2021, The Authors. All rights reserved.

关键词： Vortex flow

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