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42nd Chinese Control Conference, CCC 2023

作者： Fang, Kangyue Wu, Yunkai Zhou, Yang Zhu, Zhiyu Zeng, Qingjun College of Automation Jiangsu University of Science and Technology Zhenjiang212100 China School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang212100 China

ISBN: (纸本)9789887581543

As an important part of CRH(China Railway High-speed) trains, the stability and stationarity of a suspension system is of great significance to the vehicle system. Based on the framework of probability relevant principal component analysis(PRPCA), a novel data-driven based incipient fault detection method is proposed. Firstly, simulation data including fault information is derived from Simpack-Matlab/Simulink co-simulation platform. Secondly, the real-time monitoring of high-speed train suspension system is proposed based on PRPCA theory combined with wasserstein distance. Furthermore, compared with the traditional PCA based fault detection and diagnosis (FDD) methods, the proposed PRPCA-based method has a better performance and is more suitable for actual fault data has nonlinear and non-Gaussian characteristics. Finally, according to the comparison results with other multivariate statistical analysis based methods, the incipient fault detection method proposed in this paper has a higher sensitivity to the incipient spring/damping faults of CRH suspension system. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Principal component analysis

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An Integrated Logic Function Decomposition Flow for XOR-Majority Graphs

An Integrated Logic Function Decomposition Flow for XOR-Majo...

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2023 International Symposium of Electronics Design automation, ISEDA 2023

作者： Ma, Chengyu Xiao, Yong Shao, Yun Chu, Zhufei Ningbo University Faculty of Electrical Engineering Computer Science Ningbo315211 China Giga Design Automation Co. Ltd. Shenzhen518055 China

ISBN: (纸本)9798350304510

Logic function decomposition is critical to logic synthesis. In this paper, we propose an integrated logic function decomposition flow, which consists of disjoint support decomposition, exact synthesis, Shannon decomposition, and the recently proposed majority-of-three (MAJ) decomposition. Through this process, the logic function can be decomposed into any directed acyclic graph (DAG). An experimental evaluation shows that our algorithm leads to better XOR-majority graphs (XMGs) compared to state-of-the-art algorithms. Our experiments show that the proposed method achieves an average of 5% and 6% reduction in the lookup tables (LUTs) size/depth product applied to the EPFL arithmetic and random control benchmarks after LUT mapping, respectively. © 2023 IEEE.

关键词： Table lookup

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Deep Interactive Image Semantic and Instance Segmentation 12th

Deep Interactive Image Semantic and Instance Segmentation

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12th International Conference on Image and Graphics, ICIG 2023

作者： Wu, Xuzijing Yang, Pengfei Shao, Wenteng Wang, Tao Sun, Quansen School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China School of Automation Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9783031463075

Existing deep interactive segmentation methods only focus on the extraction of specific instance objects. When the target of interest to users is a category, existing methods have to perform more interactions. We take advantages of the relevance between semantic and instance segmentations, and give two definitions based on the interactive mode, i.e. interactive semantic segmentation and interactive instance segmentation, to distinguish the actual requirements of instance objects and semantic categories that users are interested in. Then, a dual-branch-based full convolutional network model is proposed to integrate the above two tasks (similar to a multi-task learning), in which the relevance between the interactive semantic and instance segmentations can be jointly explored along with a simultaneous output of potential interested semantic categories and instance objects. Vast experimental results on GrabCut, Berkeley, SBD and DAVIS datasets verified the effectiveness of the proposed method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantics

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Data-Enhanced Prediction with Decomposition and Amplitude-Aware Permutation Entropy in Distributed Computing Systems

Data-Enhanced Prediction with Decomposition and Amplitude-Aw...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yuan, Haitao Hu, Qinglong Bi, Jing Zhang, Wei Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China City University of Hong Kong Dept. of Computer Science 999077 Hong Kong College of Computer Beijing University of Technology Beijing100124 China University of Connecticut Dept. of Computer Science and Engineering StorrsCT06269 United States Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

In recent years, distributed computing has wit-nessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and inter-dependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVI for achieving high-accuracy workload prediction in distributed computing systems. SVI employs the Savitzky-Golay filter and variational mode decomposition for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVI improves the prediction accuracy by 35.4% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVI enhances the prediction accuracy of workload, CPU, and memory by 62.5%, 65.6%, and 69.1 %, respectively. © 2024 IEEE.

关键词： Quality of service

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Gesture-Based Human-Robot Interaction Framework for Teleoperation Control of Agricultural Robot

Gesture-Based Human-Robot Interaction Framework for Teleoper...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Li, Jiehao Liu, Hongxian Luo, Xiwen Philip Chen, C.L. Yang, Chenguang College of Engineering South China Agricultural University Guangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350316308

Remote control based on data-driven has been widely studied in human-robot interaction, which converts human body movements into digital signals through somatosensory devices for teleoperation control. It is a convenient and efficient intelligent solution to handle the robot to realize the agricultural task in a complex environment. In this paper, a real-time dynamic recognition framework based on a three-dimensional convolutional neural network is designed for agricultural robot. The deep separable convolution and inverted residual structure are presented, and then a gesture classification network architecture is discussed. Finally, some demonstrations using Unitree agricultural robot are carried out to illustrate the hand gesture application with an efficient response. © 2023 IEEE.

关键词： Remote control

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Hidden dynamics and FPGA-based hardware detection of memristive Rulkov neuron

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The European Physical Journal Special Topics 2025年 1-19页

作者： Li, Haodong Min, Fuhong School of Electrical and Automation Engineering School of Computer Science and Technology and School of Artificial Intelligence Nanjing Normal University Nanjing China

Complex dynamical systems with hidden attractors exhibit extreme sensitivity to minor parameter variations and external perturbations. However, the hidden dynamics in discrete dynamical systems incorporating memristors have not been extensively studied. To accommodate this issue, this paper constructs a novel memristive Rulkov neuron (MRN) by integrating a classical Rulkov neuron with a discrete memristor autapse. First, the analysis of fixed points reveals that the MRN exhibits either infinitely many line fixed points or none, depending on the system parameter. Subsequently, bifurcation diagrams, Lyapunov exponents, phase diagrams, iterative sequences, and basins of attraction are utilized to investigate the underlying hidden dynamical behaviors. The numerical experiments demonstrate that the MRN shows hidden spiking discharge, mixed-mode discharge, hidden discharge regime transition, multistability, and antimonotonicity. Finally, an field programmable gate array (FPGA)-based hardware detection platform is developed, which supports real-time capture of hidden attractors and discharge waveforms.

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Independent Vector Analysis Based Blind Interference Reduction and Signal Recovery for MIMO IoT Green Communications

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China Communications 2022年第7期19卷 79-88页

作者： Zhongqiang Luo Mingchun Li Chengjie Li School of Automation and Information Engineering Sichuan University of Science and EngineeringYibin 644000China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and EngineeringYibin 644000China School of School of Computer Science and Technology Southwest Minzu UniversityChengdu 610041China

In application to time convolutive mixing model or frequency domain blind separation model for wireless receiving applications,frequency domain independent component analysis(FDICA)has been a very popular method but with adverse random permutation ambiguity *** order to solve this inherent problem in FDICA assisted multiple-input multiple-output orthogonal frequency-division multiplexing(MIMO-OFDM)based the Internet of Thing(IoT)systems,this paper proposes an new detection mechanism,named independent vector analysis(IVA),for realizing blind adaptive signal recovery in MIMO IoT green communication to reduce inter-carrier interference(ICI)and multiple access interference(MAI).IVA jointly implements separation work for different frequency bin data while the FDICA deals with it *** IVA,the dependencies of frequency bins can be exploited in mitigating the random permutation *** addition,multivariate prior distributions are employed to preserve the inter-frequency dependencies for individual sources,which can result in separation performance *** results and analysis corroborate the effectiveness of the proposed method.

关键词： independent vector analysis blind source separation MIMO green communications

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Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 441-454页

作者： Yongliang Yang Zhijie Liu Qing Li Donald C.Wunsch the Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China the Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA

This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear *** asymmetric output constraints and input saturation are *** asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints.A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear *** avoid the"explosion of complexity",the dynamic surface control(DSC)technique is employed to filter the virtual control signal of each *** deal with the actuator saturation,an additional auxiliary dynamical system is *** is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately *** simulation examples are conducted to verify the presented adaptive fuzzy controller design.

关键词： Asymmetric barrier Lyapunov function input saturation Nussbaum function time-varying prescribed performance

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One-shot functional photoacoustic microscopy for monitoring traumatic brain injury 16

One-shot functional photoacoustic microscopy for monitoring ...

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16th International Conference on Photonics and Imaging in Biology and Medicine, PIBM 2023

作者： Zhang, Yameng Chen, Yang Qi, Xinping Li, Weitao Department of Computer Engineering Nanjing Institute of Technology No.1 Hongjing Avenue Nanjing Jiangsu211167 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu211106 China

ISBN: (纸本)9781510667341

Photoacoustic microscopy (PAM) is a novel medical imaging technique developed rapidly in recent years with the advantages of high resolution, high contrast, and no ionizing radiation. In this study, we developed a one-shot functional photoacoustic microscopy (OS-fPAM) system for assessing traumatic brain injury (TBI). The OS-fPAM system only employed a single 532 nm nanosecond pulse laser with Raman delay optical path control, which can produce both 532 nm and 553 nm laser beams. The dual-wavelength beams were then coupled via a dichroic mirror and focused on the surface of the experimental sample. Then, the photoacoustic signal was collected and amplified in the ultrasonic signal acquisition module, and the blood oxygen saturation (sO2) image was calculated by two wavelength photoacoustic images. The feasibility of the OS-fPAM system was performed through the calibration experiments with different ratios of red ink and blue ink. Meanwhile, the OS-fPAM system can monitor microvascular structures and sO2 in the TBI model on mice for 96 hours in vivo with a spatial resolution of ∼40 μm, demonstrating the potential to evaluate rehabilitation and cerebral vascular damage. © 2023 SPIE.

关键词： Photoacoustic microscopy

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Robust Control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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