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26th International Conference on Industrial Technology, ICIT 2025

作者： Wen, Xin Liu, Zhen-Tao Chen, Dan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9798331521950

Facial expression recognition plays a key role in promoting the development of comprehensive intelligence and building friendly human-computer interaction. Due to the interference of feature noise in expression data, the lightweight facial expression recognition model with fewer parameters is difficult to learn more expression features through simple training, which limits the improvement of its recognition performance. An efficient facial expression recognition network based on Spot-adaptive Knowledge Distillation is proposed in this paper. Inspired by VoVNetV2, the network designed in this paper is lightweightly improved using Depthwise Separable Convolution and the parameter-free SimAM attention mechanism, reducing the number of parameters to 0.21 M. To further improve the recognition accuracy of the model, Spot-adaptive Knowledge Distillation is employed to improve the characterization ability of the model. The recognition accuracies of the student network designed in this paper on the KDEF and RAF-DB datasets are 93.05% and 81.17% respectively after spot-adaptive distillation. © 2025 IEEE.

关键词： Facial Expression Recognition Knowledge Distillation Lightweight Neural Network

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PID control for Aeroengine Based on Sparrow Search Algorithm

PID Control for Aeroengine Based on Sparrow Search Algorithm

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2021 China Automation Congress, CAC 2021

作者： Xu, Liang Wang, Hao Liu, Ying Xue, Wei Li, Ningning Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China National Key Laboratory for Complex Systems Simulation Beijing China BeijingAerospace Propulsion Institute Beijing China

ISBN: (纸本)9781665426473

To address the problem of aeroengine PID parameter optimization and tuning, this work employs the excellent performance of the sparrow search algorithm (SSA) with high convergence accuracy and fast convergence speed to propose a self-tuning PID control method (SSA-PID) for aeroengine parameters. Considering that the oil supply output by the actuator may have a substantial overshoot, the proposed technique adds a penalty mechanism for the overshoot at the output, designs and improves the fitness function weighted by performance indicators, and effectively avoids the possible excessive overshoot and sharp oil supply phenomenon of the engine oil supply. The SSA-PID simulates and verifies the mathematical models of the turbofan engine ' s steady-state operating points on the ground and at high altitudes. The results show that the SSA-PID control method has better parameter tuning and optimization effects, a faster speed step response, and generates a fuel supply that does not have a large overshoot, thereby proving its effectiveness and feasibility. © 2021 IEEE

关键词： Three term control systems

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Biomechanics based computer simulation of rural landscape design using remote sensing image technology

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MCB Molecular and Cellular Biomechanics 2024年第4期21卷

作者： Xing, Kun Xia, Yuqing Academy of Art and Design Anhui University of Technology Anhui Ma’anshan243032 China key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Anhui Ma’anshan243032 China

Introduction: The strategy and restoration of rural areas and landscape in biomechanics, with a particular emphasis on cellular and molecular biomechanics, is crucial for sustainable rural landscape design. At the cellular and molecular level, plants’ biomechanical properties, such as the rigidity and elasticity of cell walls, determine their growth patterns and responses to environmental factors. These properties are essential in understanding how plants can be effectively incorporated into the rural landscape to enhance its stability and functionality. Aim: The objective of this research is to develop a novel computer simulation model for rural landscape planning using remote sensing imaging technology. Research methodology: We introduce a novel Adaptive YOLOv7 method driven by Starling Murmuration search. UAVs are used to collect extensive visual data for training the model. By considering cellular and molecular biomechanics, we can analyze how the mechanical forces within plants affect their ability to resist wind, retain water, and interact with the surrounding soil and other organisms. This knowledge can be integrated into the model to better predict the long-term viability and adaptability of different plant species in the rural landscape. The combination of the 3D GIS virtual image strategy model and our proposed model, along with SM optimization, not only improves object identification but also takes into account the biomechanical aspects for more accurate simulations. Crowdsourcing helps in precisely mapping rural landscapes and structures, while the incorporation of biomechanical principles ensures better adaptability to changing environmental and ecological conditions. Findings and Conclusion: Implemented in Python software, our SM-AYOLOv7 model shows excellent performance, with metrics like f1 score (93.64%), recall (92.34%), accuracy (91.72%), and IoU (90.23%). Our method outperforms conventional ones, demonstrating enhanced accuracy and flexibility, e

关键词： computer simulation image processing plant biomechanical properties remote sensing rural landscape design starling murmuration search-driven adaptive YOLOv7 (SM-AYOLOv7)

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Adapting Human Mesh Recovery with Vision-Language Feedback

arXiv

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arXiv 2025年

作者： Xu, Chongyang Huang, Buzhen Zhang, Chengfang Feng, Ziliang Wang, Yangang College of Computer Science Sichuan University Chengdu610065 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The School of Automation Southeast University Nanjing210096 China Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Luzhou646000 China

Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image alignment due to the lack of explicit 2D-3D correspondences. In contrast, optimization-based methods align 3D models to 2D observations but are prone to local minima and depth ambiguity. In this work, we leverage large vision-language models (VLMs) to generate interactive body part descriptions, which serve as implicit constraints to enhance 3D perception and limit the optimization space. Specifically, we formulate monocular human mesh recovery as a distribution adaptation task by integrating both 2D observations and language descriptions. To bridge the gap between text and 3D pose signals, we first train a text encoder and a pose VQ-VAE, aligning texts to body poses in a shared latent space using contrastive learning. Subsequently, we employ a diffusion-based framework to refine the initial parameters guided by gradients derived from both 2D observations and text descriptions. Finally, the model can produce poses with accurate 3D perception and image consistency. Experimental results on multiple benchmarks validate its effectiveness. The code will be made publicly available. © 2025, CC BY.

关键词： Mesh generation

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Hydrodynamic Analysis and Verification of an Innovative Whale Shark-like Underwater Glider

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Journal of Bionic Engineering 2020年第1期17卷 123-133页

作者： Huijie Dong Zhengxing Wu Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents an innovative design for a biomimetic whale shark-like underwater glider aiming at the combination of high maneuverability and long *** a hybrid of the underwater glider and the robotic fish,its pectoral fins and tail can serve as not only the external control surfaces for attitude regulation during gliding but also the propellers for agile fish-like swimming *** verify the gliding capability of the whale shark-like glider and prepare for future dynamic analysis,the hydrodynamic coefficients,including drag,lift,sliding force,and corresponding moments are estimated through computational fluid dynamics *** addition,the hydrodynamic analyses of the proposed glider and an equivalent conventional glider during steady gliding motion are executed for *** experiments are performed to verify the downward gliding *** results reveal that the whale shark-like glider has less drag as well as higher lift-to-drag ratio and a markable gliding capability in *** may offer important inspiration for improving the gliding efficiency and performance of an underwater glider in biomimetic shape design.

关键词： biomimetic robot CFD hydrodynamic analysis underwater glider

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Distribution of Temperature and Characteristics of Soot Volume Fraction in MILD-OCC Flame 9th

Distribution of Temperature and Characteristics of Soot Volu...

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9th International Symposium on Coal Combustion, ISCC 2019

作者： Lu, Jingwen Zhang, Shuwei Tan, Longhui Lu, Jianyi Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering North China Electric Power University Baoding071003 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789811616563

Coal and methane were burnt in the MILD-OCC combustion flame under different combustion conditions to study the temperature distribution and characteristics of soot volume fraction. In this experiment, the flame temperature distribution is measured by thermocouple and the volume fraction (fv) of soot at each sampling point is calculated, then combining with the mass concentration of soot by the filter weighing method to obtain the distribution characteristics of soot in the flame. The results of thermocouple particle densitometry (TPD) show that the formation and oxidation of soot at every point in the flame is related closely to its position and temperature in the flame. The fv of soot in the center of the flame is negatively correlated with the temperature of the flame during the MILD-OCC combustion. The lower temperature region of the flame is conducive to the growth of soot, which leads to higher value of fv. The higher temperature in the center of the flame is beneficial to the oxidation of the soot particles, resulting to lower value of fv. The results of the filter membrane weighing method show that the formation of soot mainly occurs in the central region of the flame. When the radial distance increases, the flame temperature rises, and the soot concentration decreases due to oxidation. On the whole, the distribution of soot measured by the filter membrane weighing method is roughly consistent with that calculated by the TPD, which provides a reference for further research on the MILD-OCC combustion. © 2022, Tsinghua University Press.

关键词： Thermocouples

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Lane-Change Intention Prediction of Surrounding Vehicles Using BiLSTM-CRF Models with Rule Embedding

Lane-Change Intention Prediction of Surrounding Vehicles Usi...

引用

Chinese Automation Congress (CAC)

作者： Kai Wang Jie Hou Xianlin Zeng Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Predicting lane-change intentions of surrounding vehicles can effectively help autonomous vehicles reduce collisions caused by lane changes and ensure driving safety. Because prediction methods based on black-box models will lead to passengers’ distrust of machine prediction, the intention prediction methods used to autonomous driving need to be interpretable and trustworthy. This paper presents a method for intention prediction of surrounding vehicles by using a bidirectional long short term memory network (BiLSTM) with a conditional random field (CRF) layer above it. Compared with intention prediction methods using deep network, the proposed method can find the features that contribute most to the prediction, thereby improving the interpretability and ensuring the prediction performance. In addition, by employing the transfer characteristic of the CRF layer, traffic rules and the experience of skilled drivers can be embedded to the prediction in the form of rules. Use rules to constrain the intention prediction, thereby improving the trustworthiness of prediction results. Test results on naturalistic driving dataset show that the proposed method can predict the lane-change intention with an accuracy of 97.22%, which is higher than that of Bi-LSTM.

关键词： Training Road transportation Knowledge engineering Predictive models Safety Autonomous vehicles Standards

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H∞ state estimation for delayed neural networks via variable-augmented-based free-weighting matrices method

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Journal of the Franklin Institute 2025年第7期362卷

作者： Chang, Xu-Kang He, Yong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The issue of H∞ state estimation for neural networks with time-varying delays is investigated in this study. Firstly, an augmented Lyapunov-Krasovskii functional (LKF) with two delay-product-type terms is constructed to enhance the consideration of system state, delay, and delay derivative information. Furthermore, for taking into account more effective information, the LKF is augmented with both single and double integral variables. Accordingly, the LKF derivative becomes a higher-order term that exhibits nonlinear characteristics of the time delay. To solve the nonlinear problem, a variable-augmented-based free-weighting-matrices (VAFWMs) approach is employed to transform the nonlinear term into a linear form and provides more freedom in obtaining less-conservative results. Consequently, two improved H∞ state estimation criteria are derived. Lastly, a numerical example is provided to demonstrate the merits and effectiveness of the presented methods. Meanwhile, to prove the practical viability of the presented methods, this study extends the methods to a real-world quadruple-tank process system. © 2025 The Franklin Institute

关键词： Lyapunov functions

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Anomaly detection in digital twin model 1

Anomaly detection in digital twin model

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Wang, Yutong Cao, Yansong Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665433372

As the simulation model of a physical system, digital twin has been widely used in many complicated control systems. Providing an effective way to perform simulation, digital twin makes the evaluation, prediction and optimization process cheaper and easier than on physical systems. For smart manufacturing, digital twin achieves high productivity with less operation and maintenance cost. However, the advantages of digital twin in anomaly detection during manufacturing are always neglected. Taking a two-speed transmission system as an example, we generate three kinds of faults on this digital twin model. After extracting features from the system output, we train an anomaly detection model on these features to classify each type of fault. By this digital twin model, we can find the fault in the whole system at the very beginning, and reduce the time and cost of debugging and diagnosing. © 2021 IEEE.

关键词： Anomaly detection

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