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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2022)

作者： D. Fu T. Zhou T. Yang T. Zhang J. Dong Key Laboratory of Networked Control Systems Institutes for Robotics and Intelligent Manufacturing Digital Factory Department Shenyang Institute of Automation Chinese Academy of Sciences Shenyang People's Republic of China Technical Management Division Guodian Technology & Environment Group Co Ltd. Beijing People's Republic of China Digital Factory Department Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang People's Republic of China

Biofuel-based heat sources are gradually penetrated into heating systems in Northern China in the background of carbon neutrality. It is essential to conduct biofuel risk management study, not only for enhancing the ability of continuous heat supply for heating systems, but also improving the ability of effective cost control. A biofuel risk management model is thus proposed innovatively for biomass-based heat sources considering supply-demand-side uncertainties. The developed model integrates Chance-constrained programming, Two-stage stochastic programming and the traditional linear programming into a general framework. After that, the developed model is applied in to a real heat-source case of biofuel risk management under uncertainties and the corresponding solutions on biofuel risk management are generated. The beneficial results of biofuel allocation pattern can be obtained for decision-makers to provide the fuel management support under different risk levels. Besides, a trade-off analysis between the constraint-violation risk and the system cost can also be provided to conduct in-depth analysis.

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Multimode Industrial Process Monitoring using Hierarchical Mode Division and Serial Independent Component Analysis

Multimode Industrial Process Monitoring using Hierarchical M...

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第32届中国过程控制会议(CPCC2021)

作者： Shuai Li Xiaofeng Zhou Haibo Shi Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences

With the increasing scale and complexity,how to analyze the hybrid characteristics including multimode,nonGaussianity and nonlinearity is one of the most difficult problems faced by multimode industrial process *** paper proposes a monitoring method using hierarchical mode division with serial independent component analysis for multimode processes with *** the multimodal uncertainty and transition mode,hierarchical mode information with transitions is first obtained by mode division using hierarchical density peaks ***,by integrating independent component analysis(ICA) and kernel independent component analysis(KICA) using the serial structure,a hybrid non-Gaussian and nonlinear process modeling method using serial independent component analysis is used for hierarchical process ***,the stable and transition mode identification using geodesic distance is developed for multimode industrial process *** monitoring results for the penicillin fermentation process show the feasibility and effectiveness.

关键词： Process monitoring multimode industrial process transition mode hierarchical mode division serial independent component analysis

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Design and implementation of FPGA-based hardware acceleration system for target detection

Design and implementation of FPGA-based hardware acceleratio...

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Chinese Automation Congress (CAC)

作者： Canyu Zhan Bingjie Zhao Huangliang Zhang Zhongpeng Yan Jie Wu Da Yuan Shenyang University of Chemical Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China Shenyang University of Technology Shenyang China

Since the application of target detection in convolutional neural networks is becoming more and more widespread, and the computational volume is increasing, the complexity of the network hierarchy and the memory requirements are gradually increasing, so according to the Field Programmable Gate Array (FPGA) parallel computing characteristics, using FPGA to accelerate the convolutional neural network hardware, can design a CPU+FPGA target detection hardware acceleration system. The system adopts the YOLOv2 target detection algorithm and divides the tasks according to the network structure of the algorithm, and at the same time, it quantifies the 32-bit floating-point numbers of the algorithm with 16-bit fixed points, optimizes the convolutional, pooling, and reordering layers of the algorithm, and finally designs the algorithm by using the HLS high-level synthesis. The system uses PYNQ-Z2 platform to implement the convolutional neural network YOLOv2, and the final system performance reaches 27.06GOPs (Giga Operations Per Second, 1 billion operations/s), and the power consumption is only 2.609W, compared to CPU (E5-2620V4), its performance is 6.58 times that of CPU, and the power consumption is only 3% of the CPU, which has certain advantages compared with current target detection systems.

关键词： Power demand System performance Software algorithms Object detection Software System-on-chip Convolutional neural networks

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Identifiability Analysis of Noise Covariances for LTI Stochastic systems with Unknown Inputs

arXiv

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arXiv 2022年

作者： Kong, He Sukkarieh, Salah Arnold, Travis J. Chen, Tianshi Mu, Biqiang Zheng, Wei Xing Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen518055 China Sydney Institute for Robotics and Intelligent Systems The University of Sydney NSW2006 Australia Madison WI53704 United States School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Computer Data and Mathematical Sciences Western Sydney University SydneyNSW2751 Australia

Most existing works on optimal filtering of linear time-invariant (LTI) stochastic systems with arbitrary unknown inputs assume perfect knowledge of the covariances of the noises in the filter design. This is impractical and raises the question of whether and under what conditions one can identify the process and measurement noise covariances (denoted as Q and R, respectively) of systems with unknown inputs. This paper considers the identifiability of Q/R using the correlation-based measurement difference approach. More specifically, we establish (i) necessary conditions under which Q and R can be uniquely jointly identified;(ii) necessary and sufficient conditions under which Q can be uniquely identified, when R is known;(iii) necessary conditions under which R can be uniquely identified, when Q is known. It will also be shown that for achieving the results mentioned above, the measurement difference approach requires some decoupling conditions for constructing a stationary time series, which are proved to be sufficient for the well-known strong detectability requirements established by Hautus. © 2022, CC BY.

关键词： Stochastic systems

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Event-triggered state estimation for T-S fuzzy affine systems based on piecewise Lyapunov-Krasovskii functionals

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control Theory and Technology 2019年第1期17卷 99-111页

作者： Meng WANG Jianbin QIU Gang FENG Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong China State Key Laboratory of Robotics and Systems & Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China

This paper investigates the problem of event-triggered H∞state estimation for Takagi-Sugeno (T-S) fuzzy affine systems. The objective is to design an event-triggered scheme and an observer such that the resulting estimation error system is asymptotically stable with a prescribed H∞performance and at the same time unnecessary output measurement transmission can be reduced. First, an event-triggered scheme is proposed to determine whether the sampled measurements should be transmitted or not. The output measurements, which trigger the condition, are supposed to suffer a network-induced time-varying and bounded delay before arriving at the observer. Then, by adopting the input delay method, the estimation error system can be reformulated as a piecewise delay system. Based on the piecewise Lyapunov-Krasovskii functional and the Finsler's lemma, the event-triggered H∞observer design method is developed. Moreover, an algorithm is proposed to co-design the observer gains and the event-triggering parameters to guarantee that the estimation error system is asymptotically stable with a given disturbance attenuation level and the signal transmission rate is reduced as much as possible. Simulation studies are given to show the effectiveness of the proposed method.

关键词： Takagi-Sugeno (T-S) fuzzy affine systems event-triggered scheme, piecewise Lyapunov-Krasovskii functional, state estimation

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Research on fault feature extraction of rotating machinery based on adaptive VMD and optimized CYCBD

Research on fault feature extraction of rotating machinery b...

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Chinese control and Decision Conference, CCDC

作者： Ran Xie Ling Xiong Binbin Dan Zeyu Ren Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China Key Laboratory of Metallurgical Equipment and Control of Ministry of Education Wuhan China School of Physics and Electronic Science Hunan Institute of Science and Technology Yueyang China

ISBN: (纸本)9781665478977

To solve the problem that early fault features of rotating machinery are difficult to extract, an adaptive k-value hierarchical variational mode decomposition (H-VMD) combined with optimized maximum second-order cyclostationarity blind deconvolution (CYCBD) fault feature extraction method is proposed in this paper. Mode decomposition of the vibration signal is performed with H-VMD. and then the noise dominant component is denoised by wavelet threshold denoising (WTD). Furthermore, the improved autocorrelation-weighted correlated kurtosis (ACK) when CYCBD enhances the periodic shock component of the denoised signal is the fitness function of ChOA, and the envelope demodulation analysis of the feature-enhanced signal is performed using the teager energy operator (TEO). Simulation analysis and experimental results show that the interference of background noise can be effectively removed and the periodic shock component of the vibration signal be enhanced by the proposed method, which is a new feature extraction method for the fault diagnosis of rotating machinery.

关键词： Vibrations Fault diagnosis Electric shock Noise reduction Interference Feature extraction Linear programming

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When measurements fail: using an interactive SLAM solution to fight bad odometry

When measurements fail: using an interactive SLAM solution t...

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IEEE Instrumentation and Measurement Technology Conference

作者： Robert Milijaš Juraj Oršulić Stjepan Bogdan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9781728144603

ISBN: (纸本)9781728144610

In this paper we use the underlying pose graph structure of graph SLAM to allow the user to inspect and intervene into the Simultaneous Localization and Mapping (SLAM) process. With post-processing the map by inserting custom constraints into the optimization problem, the user can improve the quality of the map obtained as the final SLAM result. We refer to this inspection and intervention process as interactive SLAM. The mathematical background, which allows such interventions, is laid out, and a software implementation is used to improve the quality of a map created at the Faculty of Electrical Engineering and Computing, University of Zagreb.

关键词： SLAM robotics Interactive SLAM supersonic low altitude missile robotics maps software implementation ELECTRICAL ENGINEERING odometry

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Edge computing-based defect identification model of power IoT edge side devices

Edge computing-based defect identification model of power Io...

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2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Li, Dawei Jia, Gengtao Song, Chunhe Yu, Shimao Start Grid Shanghai Information Telecommunication Company Shanghai200122 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang11016 China

ISBN: (纸本)9781728152240

There are various types of devices on the terminal side of the power Internet of Things, and the data collected through various sensors shows an exponential growth. The current in-depth application of edge computing technology can not only ease the pressure of network transmission, but also improve the timeliness of fault diagnosis. Edge computing technology is A new way to solve the fault diagnosis of equipment on the edge of the power grid. From the perspective of edge fault diagnosis, this paper expounds the fault diagnosis model of power IoT edge devices based on edge computing, and combines the isolated forest algorithm to design smart sensor data-based power IoT edge device fault diagnosis algorithms. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Failure analysis

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Distributed computing framework of intelligent sensor network for electric power internet of things 9

Distributed computing framework of intelligent sensor networ...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Dawei Yu, Ruimo Song, Chunhe Li, Shu Jia, Gengtao Zhou, Xiaoli Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

The power IoT terminal environment is complex, and current smart sensor sensors have problems such as poor networking capabilities and large processing delays, and few specific edge-side automatic networking capabilities. This paper analyzes and elaborates the distributed intelligent sensor computing framework from the perspective of edge intelligent networking, designs a computing model for intelligent sensors of power Internet of Things terminals, and gives the edge-based deployment of convolutional neural network architecture, data aggregation, model training, and intelligent reasoning. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Internet of things

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Application of Complementary Sliding Mode control with State Observer in Servo System of Voice Coil Motor

Application of Complementary Sliding Mode Control with State...

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第34届中国控制与决策会议

作者： Yang Liu Danping Jia Bingjie Zhao Tao Zhang Hualiang Zhang Hongyu Yan Xu Lu School of Artificial Intelligence Shenyang University of Technology School of Information Science and Engineering Shenyang University of Technology Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrica l Engineering Dalian University of Technology

ISBN: (纸本)9781665478977

Due to the vulnerability of the voice coil motor(VCM) servo system to uncertain elements such as external disturbance,nonlinear friction,and inherent end impact,a dynamic model of the linear servo motor motion system with uncertainty is *** complementary sliding mode variable structure controller(CSMC) is built on the basis of the standard sliding mode control by merging the generalized sliding mode surface with the complimentary sliding mode *** study demonstrates that this controller can ensure the system's tracking error converges,suppresses uncertain factors,increases the system's transient reaction speed,and successfully reduces tracking ***,the saturation function is chosen as the switching function,which mitigates the sliding mode control chattering *** total interference is defined as the unmeasured and unknown interference in the mathematical model of the *** system's position and total disturbance are estimated using the nonlinear extended state observer(ESO).The estimated total disturbance is then feed-forward corrected to the control *** a result,a nonlinear extended state observer-based closed-loop complementary sliding mode position control technique is ***,the system experiment demonstrates the effectiveness and feasibility of the suggested control *** complimentary sliding mode control system with state observer offers a high degree of tracking accuracy and robustness,which considerably minimizes the system's tracking error.

关键词： Voice coil motor Complementary sliding mode control Extended state observer Servo system

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