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第37届中国控制会议

作者： Hongxu Zhang Jun Hu Lei Zou Department of Applied Mathematics Harbin University of Science and Technology School of Measurement and Communication Harbin University of Science and Technology The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology School of Engineering University of South Wales College of Electrical Engineering and Automation Shandong University of Science and Technology

In this paper, we address the event-triggered state estimation problem for a class of time-varying complex networks subject to multiplicative noises and stochastic coupling under uncertain occurrence probability. The stochastic coupling is modeled by introducing a set of Bernoulli distributed random variables, where the uncertainties of the occurrence probability is characterized. Moreover, the event-triggered mechanism is employed with hope to reduce the network burden and save energy consumption. The aim of the paper is to design the robust state estimator for addressed dynamics networks and derive an optimized upper bound of the estimation error covariance by properly choosing the estimator gain. Finally, simulations and comparisons are provided to verify the validity of the proposed robust state estimation method.

关键词： Stochastic coupling networks State estimation Event-triggered mechanism Multiplicative noises Uncertain occurrence probability

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State Estimation and Fault Detection for Nonlinear Dynamic Systems

State Estimation and Fault Detection for Nonlinear Dynamic S...

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第37届中国控制会议

作者： Baohua Lu Liping Yan Hongxue Chen Yuanqing Xia Mengyin Fu Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

In practical problems, the dynamic systems are usually nonlinear. In this case, the traditional Kalman filter cannot be used for state estimation or fault detection. The two typical extension based on Kalman filtering framework is the Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF). Theoretically speaking, UKF is better than EKF when estimation accuracy is concerned, especially for high degree nonlinear cases. This paper is concerned with the state estimation and fault detection problem for a class of nonlinear dynamic systems. A novel fault detection and analyse method is presented based on the period residual of EKF and UKF. For different kind of faults, mainly, the system parameter error, the sensor/data error, EKF and UKF are used, and the estimation and fault detection effects are compared and analyzed.

关键词： nonlinear system state estimation fault detection parameter error sensor error

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Optimization of the Circuit Parameter in Class-E Power Amplifier in the Two-coil Wireless Power Transfer System

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IOP Conference Series: Materials Science and engineering 2020年第1期740卷

作者： Zhuang Sun Qing Liu Kun Li Bin Hu Haibo Zhao Yankai Shi Shijie Zhang Yang Liu Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China Tianjin Institute of Power Sources Tianjin China

In this paper, the circuit parameters of the Class-E power amplifier are investigated and optimized to achieve the maximum of output power and efficiency in a two-coil Wireless Power Transfer (WPT) system. The circuit is simulated with software named Saber. Working frequency, the value of capacitors and inductor, which has relationship with the output power and efficiency, are investigated during the simulation. With the simulation results, it is found that the frequency and the shunt capacitor need to be optimized for high performance of the wireless power transfer system.

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Research on 4G And 5G Authentication Signaling

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Journal of Physics: Conference Series 2019年第4期1213卷

作者： Lei Song Zhan Xu Zhigang Tian Jinhui Chen Ruxin Zhi School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education

In recent years, the development and standardization of 5G networks have received extensive attention. 3GPP officially confirmed that Service-Based Architecture (SBA) is the unified infrastructure of the 5G core network (5GC). The Service-Based Interface (SBI) is an important part of the SBA for interaction between network function services within the 5GC. The fifth generation mobile network will support a range of use cases and requirements that are completely different from traditional 4G networks, such as providing a high level of authentication mechanisms. This paper is organized as follows: First, we compare the difference between 4G authentication and 5G authentication in three aspects including the 4G architecture, authentication process, and communication protocol stack, then implement the simulation environment, and finally evaluate the performance by comparing the delay.

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Electromechanical control Based On Artificial Neural Network

Electromechanical Control Based On Artificial Neural Network

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ming-Chao Yu Gong-Fa Li Ying Sun Bo Tao Guo-Zhang Jiang Shuang Xu Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Wuhan China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan China D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781538652152

According to the gradual rise of current theoretical research on artificial neural network, this article made a preliminary overview of the application of the artificial neural network control system, and then combined with the problems of intelligent electromechanical control field, to discuss the application method of artificial neural network in the control system of electromechanical integration. This paper first introduces the background of artificial neural network and electromechanical integration, and then summarizes the status quo of expert system, fuzzy logic and neural network applied in the electromechanical integration control system in the field of artificial intelligence. Then, this paper focuses on how to combine artificial neural network with electromechanical control system, and analyzes the advantages and disadvantages and practical application prospects of artificial neural network. Finally, some problems that may be further improved by artificial neural network in the field of electromechanical control are put forward, and a preliminary prospect for its future application value is made.

关键词： control systems Artificial neural networks Mechatronics Biological neural networks Expert systems Process control

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An Improved Real-Time Approach for Video based Angular Motion Detection and measurement

An Improved Real-Time Approach for Video based Angular Motio...

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IEEE International Conference on Computational Intelligence and Computing Research

作者： Anirudha V Bharadwaj Suraj Paul L. Ravi Kumar A Somanathan Electronics and communication Engineering Ramaiah Institute of Technology Bangalore India Control Dynamics and Simulation Group U. R. Rao Satellite Center (URSC) Bangalore India

ISBN: (纸本)9781538615096

Angular Velocity(AV) estimation is necessary for controllers used for rotation motion monitoring. The velocity estimated is used for feedback and is very crucial in speed control for a variety of applications such as spacecraft tumbling detection, propeller speed control etc. Linear motion detection and linear velocity estimation has been exploited vastly. But, when it comes to angular velocity estimation of a randomly moving object with varying angular speeds, computation is very complex. Hence, computation of AV by non-contact based methods are in huge demand. The need for detection of the direction and value of rotation of a tumbling spacecraft in the Earth's orbit is a huge necessity. Accurate AV estimation has applications in spacecraft docking in space. In the proposed work we have developed an improved algorithm for real-time estimation of rotation using live video feed. The AV of the object can be measured by the camera feed of the rotating bodies as grabbed by the video camera. Angle is computed on every frame with respect to a reference and monitored for a certain number of frames to give the instantaneous AV. The number of frames processed by the camera is dynamic and is estimated prior to the angle calculation. Comparison of performance of AV estimation by the proposed algorithm with state-of-the-art Lucas Kanade(LK) object tracking method based AV estimation is also reported. The proposed approach shows significant improvement in estimating velocities whose motion is circular in nature. Additionally, this work advocates a novel approach towards an effective real-time angular velocity calculation by thresholding techniques, blob identification, and centroid detection.

关键词： Estimation Image color analysis Real-time systems Cameras Angular velocity Image segmentation Satellites

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International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Canfei Sun Youren Wang Yong Shen College of Automation Engineering Aviation Key Laboratory of Science and Technology on Fault Diagnosis and Health Management Nanjing China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Shanghai Aero Measurement & Control Technology Research Institute Shanghai China

ISBN: (纸本)9781538660584;9781538660577

Planetary gear train fault diagnosis is critical to Prognostics and Health Management of the helicopter. Generally, the localized gear fault will cause periodic impulses in the vibration signal. However, the fault characteristic generated by incipient fault is often weak and submerged in strong background noise, resulting in difficulty in fault feature extraction. To address this issue, a method combining Maximum Correlated Kurtosis Deconvolution(MCKD) and Overlapping Group Shrinkage(OGS) algorithms is proposed. Firstly, Fruit fly Optimization Algorithm(FOA) was employed to search for the optimal influencing parameters of MCKD, and the impulses of the raw fault signal could be enhanced after processed by MCKD adaptively. Then, the deconvolution signal was further processed by OGS to eliminate the residual noise. Finally, the fault characteristic frequency components could be identified by analyzing the envelope spectrum of the filtered signal, and achieved the incipient fault diagnosis of helicopter planetary gear. The proposed method is validated using the vibration signal of the planetary gear train in a helicopter transmission test rig, and a slight cracked planetary gear fault is successfully identified.

关键词： Gears Fault diagnosis Vibrations Deconvolution Helicopters Feature extraction Noise measurement

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A Parameter-Irrelevant Range-Based Normalized Wireless Positioning Algorithm

A Parameter-Irrelevant Range-Based Normalized Wireless Posit...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Jie-Tai Wang Xiao-Niu Yang Zhen-Xing Luo Mathematics Physics and Information Engineering College Jiaxing University Jiaxing China Science and Technology on Communication Information Security Control Laboratory 36 Research Institute of CETC Jiaxing China

This paper proposes a ranging-based positioning method independent of environmental factors and compensation coefficients. This method uses the normalized RSSI and distance model to shield the influence of parameters A and n, and then compare the normalized algorithm with the fingerprint algorithm and Min-Max algorithm, the result proves the effectiveness and advancement of the proposed algorithm.

关键词： Computational intelligence

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State Estimation and Fault Detection for Nonlinear Dynamic Systems

State Estimation and Fault Detection for Nonlinear Dynamic S...

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Chinese control Conference (CCC)

作者： Baohua Lu Liping Yan Hongxue Chen Yuanqing Xia Mengyin Fu Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In practical problems, the dynamic systems are usually nonlinear. In this case, the traditional Kalman filter cannot be used for state estimation or fault detection. The two typical extension based on Kalman filtering framework is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Theoretically speaking, UKF is better than EKF when estimation accuracy is concerned, especially for high degree nonlinear cases. This paper is concerned with the state estimation and fault detection problem for a class of nonlinear dynamic systems. A novel fault detection and analyse method is presented based on the period residual of EKF and UKF. For different kind of faults, mainly, the system parameter error, the sensor/data error, EKF and UKF are used and the estimation and fault detection effects are compared and analyzed.

关键词： Fault detection Mathematical model State estimation Kalman filters Nonlinear systems Jacobian matrices

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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

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Physical Review X 2023年第4期13卷 041039-041039页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith S. Akcay T. Akutsu S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud M. Arogeti S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. Brandt J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer G. S. Cabourn Davies L. Cadonati G. Cagn LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India University College Dublin Dublin 4 Ireland Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut L

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

关键词： Gravitational waves

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