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Chinese Automation Congress (CAC)

作者： Ziai Zhou Hao Wu Ya Zhang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665426480

This paper mainly studies the distributed robust filtering problem for wireless sensor networks without knowing the variance of the driving noise and measuring noise. A distributed filtering algorithm based on leader-follower consensus strategy is developed. Firstly, from limited sampling data of noises, the empirical distribution of the noises which play a critical role in filtering is given. Secondly, by formulating the problem as a zero-sum game problem and using dynamic programming approach, an optimal distributed robust filtering policy with Wasserstein penalty for the leader is obtained. Then, by using an adaptively weighting average consensus protocol, the filtering algorithm for followers is given. The effectiveness of the proposed filter is demonstrated through simulations.

关键词： Wireless sensor networks Costs Estimation Switches Filtering algorithms Information filters Robustness

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Multi-segment Bidding Behaviors of Power Units: Price-capacity-pair Analysis and Modeling 36

Multi-segment Bidding Behaviors of Power Units: Price-capaci...

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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Hou, Shuangshuang Wang, Ying Li, Lili Zhao, Jing Ning, Jia Zhang, Kaifeng Southeast University College of Software Suzhou China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China State Grid Electric Power Research Institute Nari Group Corporation Nanjing China Nanjing Institute of Technology School of Electric Power Engineering Nanjing China

ISBN: (纸本)9781665437127

With the deregulation of the power market, power units are allowed to make strategic biddings. The bidding results of the strategic bidding market are substantially different from the ones in the previous regulated market. Such differences in the bidding results will further have impacts on the power flow and system security. Thus, it is important to analyze and establish a model to simulate the bidding behaviors of the power units. This paper proposes a price-capacity-pairs model to simulate multi-segment bidding behavior. We select five vital factors that affect biddings behaviors as input: load, capacity, supply-demand ratio, bidders' bidding tendency and unit type. Based on the three-segment bidding rule, the price-capacity pair is used. For uncertain price or capacity, we choose a truncated normal distribution model. Scenario generation and reduction are achieved by Monte Carlo simulation and fuzzy C-means clustering algorithm. We apply our method to a case study based on Guangdong's market in China. The simulation of wind power units, coal power units and gas power units has verified the correctness of the model. © 2021 IEEE.

关键词： Power markets

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Nonlinear Model Predictive Clamping Force control for Electromechanical Brake System

Nonlinear Model Predictive Clamping Force Control for Electr...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Wenpeng Wei Tianyi He Yifan Men Jinxiang Wang Lu Xiong Guodong Yin Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Mechanical Engineering Southeast University Nanjing China Department of Mechanical and Aerospace Engineering Utah State University Logan UT USA ZDrive.ai 7th Floor Block T2 Ali Center 1398 Shenchang Road Minhang District Shanghai China School of Mechanical Engineering Southeast University Nanjing China School of Automotive Studies Tongji University Shanghai China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

In this paper, the problem of clamping force control for the Electromechanical Brake (EMB) system in autonomous vehicles is addressed. A nonlinear model predictive control framework is proposed to solve for the optimal maneuver at each optimization step to realize accurate clamping force tracking. First, the EMB system is modeled to a state-space representation through the first-principle modeling; Second, a control framework that includes three blocks is proposed to achieve clamping force tracking. The first block designs a clamping force separation strategy and an unknown input observer based on Kalman filter is applied to estimate the clamping force to replace the force sensors; the second block develops an adaptive estimation of polynomial coefficients to deal with the time-varying coefficients to improve model adaptiveness; the last block conceives the nonlinear model predictive control to track the reference force, and the resulted nonlinear programming is solved by the multiple shooting method. Finally, the proposed framework is validated to achieve faster tracking speed and more accurate tracking in multiple simulation scenarios.

关键词： Adaptation models Force Predictive models Observers Prediction algorithms Polynomials Clamps Kalman filters Force control Predictive control

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Prediction model for mechanical properties of hot-rolled strips by deep learning

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Journal of Iron and Steel Research International 2020年第9期27卷 1045-1053页

作者： Wei-gang Li Lu Xie Yun-tao Zhao Zi-xiang Li Wen-bo Wang Engineering Research Center of Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and TechnologyWuhan 430081HubeiChina Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and TechnologyWuhan 430081HubeiChina Hubei Province Key Laboratory of Systems Science in Metallurgical Process Wuhan University of Science and TechnologyWuhan 430081HubeiChina

The prediction of the mechanical properties of hot-rolled strips is a very complex,highly dimensional and nonlinear problem,and the published models might lack reliability,practicability and ***,a new model was proposed for predicting the mechanical properties of hot-rolled strips by deep ***,the one-dimensional numerical data were transformed into two-dimensional data for expressing the complex interaction between the influencing ***,a new convolutional network was proposed to establish the prediction model of tensile strength of hot-rolled strips,and an improved inception module was introduced into this network to abstract features from different *** comparative experiments were carried out to find the optimal network structure and its ***,the prediction experiments were carried out on different models to evaluate the performance of the new convolutional network,which includes the stepwise regression,ridge regression,support vector machine,random forest,shallow neural network,Bayesian neural network,deep feed-forward network and improved LeNet-5 convolutional neural *** results show that the proposed convolutional network has better prediction accuracy of the mechanical properties of hot-rolled strips compared with other models.

关键词： Deep learning Convolutional neural network Mechanical property Hot-rolled strip

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Smoke vehicle detection based on multi-feature fusion and hidden Markov model

Smoke vehicle detection based on multi-feature fusion and hi...

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作者： Tao, Huanjie Lu, Xiaobo School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

Existing smoke vehicle detection methods and vision-based smoke detection methods are vulnerable to false alarms. This paper presents an automatic smoke vehicle detection method based on multi-feature fusion and hidden Markov model (HMM). In this method, we first detect moving objects using an improved visual background extractor (ViBe) algorithm and obtain smoke-colored blocks using color histogram features in the HSI (hue, saturation, and intensity) color space. The adaptive scale local binary pattern (AS-LBP) and the discriminative edge orientation histogram (disEOH) are proposed and combined to characterize the smoke-colored blocks. More specifically, the proposed AS-LBP, a texture feature descriptor, is based on the quadratic fitting of our labelled data to obtain the best scale. The proposed disEOH, a gradient-based feature descriptor, is robust to noise by extracting discriminative edge information using Gaussian filters and principal component analysis (PCA). The discrete cosine transform (DCT) is employed to extract frequency domain information from the region fused by smoke blocks. To utilize the dynamic features, the HMMs are employed to analyze and classify the smoke-colored block sequences and region sequences in continuous frames. The experimental results show that the proposed method achieves better performances than existing smoke detection methods, especially achieves lower false alarms. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Smoke

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Secrecy Performance Analysis of Multi-Functional RIS-Assisted NOMA Networks

arXiv

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arXiv 2024年

作者： Pei, Yingjie Ni, Wanli Xu, Jin Yue, Xinwei Tao, Xiaofeng Niyato, Dusit School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China Key Laboratory of Information and Communication Systems Ministry of Information Industry China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing102206 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

Although reconfigurable intelligent surface (RIS) can improve the secrecy communication performance of wireless users, it still faces challenges such as limited coverage and double-fading effect. To address these issues, in this paper, we utilize a novel multi-functional RIS (MF-RIS) to enhance the secrecy performance of wireless users, and investigate the physical layer secrecy problem in non-orthogonal multiple access (NOMA) networks. Specifically, we derive the secrecy outage probability (SOP) and secrecy throughput expressions of users in MF-RIS-assisted NOMA networks with external and internal eavesdroppers. The asymptotic expressions for SOP and secrecy diversity order are also analyzed under high signal-to-noise ratio (SNR) conditions. Additionally, we examine the impact of receiver hardware limitations and error transmission-induced imperfect successive interference cancellation (SIC) on the secrecy performance. Numerical results indicate that: i) under the same power budget, the secrecy performance achieved by MF-RIS significantly outperforms active RIS and simultaneously transmitting and reflecting RIS;ii) with increasing power budget, residual interference caused by imperfect SIC surpasses thermal noise as the primary factor affecting secrecy capacity;and iii) deploying additional elements at the MF-RIS brings significant secrecy enhancements for the external eavesdropping scenario, in contrast to the internal eavesdropping case. Copyright © 2024, The Authors. All rights reserved.

关键词： Budget control

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A Domain Generalization Method for E-nose Cross-platform Identification of Ignitable Liquids

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IEEE Sensors Journal 2025年

作者： Song, Tian-Shu Hou, Hui-Rang Chen, Zhen-Peng Ding, Hui-Hang Meng, Qing-Hao Tianjin University Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin300072 China

Electronic nose (e-nose) can carry out odor fingerprinting and identification, exhibiting several advantages such as speed, low cost and portability. The e-nose technology allows objective, accurate and real-time detection and recognition of ignitable liquids (ILs), which provide technical support for fire cause determination and fire scene reproduction. Metal oxide semiconductor (MOS) gas sensors have certain technical limitations, and multiple e-nose platforms assembled using the same sensor array will produce different output responses when sampling the same gas. Manual data labeling and repetitive training of models involve a huge workload. This study proposes a novel domain generalization method to mitigate this problem. During the training process, we assign pseudo-domain labels iteratively for the e-nose response signals obtained from multiple source domains by clustering. This approach avoids the situation where multiple potential domains can exist for the same e-nose. The highlights of our approach are as follows: 1) The training paradigm of traditional domain generalization methods that require domain labels is not used;2) Pseudo-domain labels are generated for the samples according to each cycle iteration during training;3) The feature extractor is trained to learn domain-invariant features by adversarial learning based on pseudo-domain labels;4) The statistics of each hidden layer of the neural network are used to cluster the e-nose signals and generate pseudo-domain labels from them. Five e-noses, each with 16 identical sensor channels, are used to recognize four types of ILs. Our method achieves an average cross-platform recognition accuracy of 85.2%. © 2001-2012 IEEE.

关键词： Deep neural networks

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Performance Analysis of OMA/NOMA-aided Satellite Communication Networks: A Stochastic Geometry Approach

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IEEE Transactions on Communications 2024年

作者： Li, Kecheng Wang, Jun Hou, Tianwei Li, Anna Yue, Xinwei Liu, Yuanwei Chen, Wei School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom KU Leuven Leuven3001 Belgium School of Computing and Communications Lancaster University LancasterLA1 4WA United Kingdom Key Laboratory of Information and Communication Systems Ministry of Information Industry China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

The increasing quality of service requirements and demand for satellite services necessitate higher data rates, spectral efficiency, and stability in satellite communication networks. Therefore, this paper investigates the non-orthogonal multiple access (NOMA) assisted satellite communication networks, where multiple users are uniformly distributed over a spherical hat according to the homogeneous Poisson point process (HPPP). Based on the characteristics of HPPP, we analyze the distance distributions of users. To evaluate the performance of the proposed networks, we first derive the closed-form expressions and approximated expressions of the outage probability (OP) for paired NOMA users. To obtain more insights into the proposed networks, the ergodic rate and diversity orders for paired NOMA users are also derived. Spectral efficiency is derived for NOMA and orthogonal multiple access (OMA) assisted satellite communication networks. Our analytical results demonstrate that the diversity order of the proposed networks is all one. Numerical results confirm that: 1) compared to OMA, the proposed NOMA-assisted satellite network demonstrates superior outage performance and spectral efficiency, especially in the higher power regimes;2) fading factors have negligible effects on OP and spectral efficiency;and 3) under certain target rates for both near and far users, the outage performance of far users in NOMA-assisted satellite communication networks is superior to that of near users. © 2024 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Satellite communication systems

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Efficient Dynamic 3d Shape measurement Technique for Resisting Motion-Induced Error

SSRN

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SSRN 2022年

作者： Yao, Pengcheng Gai, Shaoyan Da, Feipeng The School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Jiangsu Nanjing210096 China Shenzhen Research Institute of Southeast University Guangdong Shenzhen518000 China

The phase-shifting profilometry is usually used to acquire dynamic 3D scenarios owning to these merits of dense 3D points, high speed, and simple devices. However, the object in motion will introduce an unknown phase shift, inducing the motion error in 3D shape. Eliminating the motion error with high efficiency is still a significant challenge. This paper analyzes the model of motion error and proposes a novel fringe projection strategy to resist the motion error. Unlike the traditional methods, typically compensating for the motion error with supplementary computing, the proposed method can directly obtain the accurate phase since the designed fringe projection strategy possesses the function of resisting motion error. Therefore, it is more efficient without the post-processing procedure. Simulations and experiments reveal that the proposed method can improve efficiency by about 300% with reasonable accuracy. © 2022, The Authors. All rights reserved.

关键词： Profilometry

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Relay Satellite Assisted LEO Constellation NOMA Communication System

arXiv

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arXiv 2024年

作者： Zhang, Xuyang Yue, Xinwei Han, Zhihao Li, Tian Shen, Xia Wang, Yafei Liu, Rongke Key Laboratory of Information and Communication Systems Ministry of Information Industry China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang Hebei050081 China Beijing100191 China School of Electronic and Information Engineering Beihang University Beijing100191 China Shenzhen Beihang Emerging Industry Technology Research Institute Shenzhen518063 China

This paper proposes a relay satellite assisted low earth orbit (LEO) constellation non-orthogonal multiple access combined beamforming (R-NOMA-BF) communication system, where multiple antenna LEO satellites deliver information to ground non-orthogonal users. To measure the service quality, we formulate a resource allocation problem to minimize the second-order difference between the achievable capacity and user request traffic. Based on the above problem, joint optimization for LEO satellite-cell assignment factor, NOMA power and BF vector is taken into account. The optimization variables are analyzed with respect to feasibility and non-convexity. Additionally, we provide a pair of effective algorithms, i.e., doppler shift LEO satellite-cell assisted monotonic programming of NOMA with BF vector (D-mNOMA-BF) and ant colony pathfinding based NOMA exponential cone programming with BF vector (A-eNOMA-BF). Two compromise algorithms regarding the above are also presented. Numerical results show that: 1) D-mNOMA-BF and A-eNOMA-BF algorithms are superior to that of orthogonal multiple access based BF (OMA-BF) and polarization multiplexing schemes;2) With the increasing number of antennas and single satellite power, R-NOMA-BF system is able to expand users satisfaction;and 3) By comparing various imperfect successive interference cancellation, the performance of A-mNOMA-BF algorithm exceeds D-mNOMA-BF. Copyright © 2024, The Authors. All rights reserved.

关键词： Satellite communication systems

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