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第34届中国控制与决策会议

作者： Jiuwu Hui Jingqi Yuan State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Department of Automation and the Key Laboratory of System Control and Information Processing/Ministry of EducationShanghai Jiao Tong University

Constraints on the control input and system states as well as uncertain disturbances are the practical challenges in many motion control *** this paper,a disturbance observer(DO) with two-step disturbance compensation algorithm is proposed to deal with disturbances and enhance the robustness of the controller,while a discrete sliding mode predictive control(DSMPC) scheme is designed to handle saturation constraints on the control input and system states with the application to an autonomous underwater vehicle(AUV).The DSMPC combines the model predictive control(MPC) with the discrete sliding mode control(DSMC) using linear matrix inequalities *** stability of the proposed DSMPC are proved via Lyapunov stability ***,simulation results are presented to illustrate the effectiveness of the whole control scheme.

关键词： Disturbance observer Two-step compensation algorithm Discrete sliding mode predictive control Inequality constraints and AUV pitch-axis motion control

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Clinical characteristics and outcomes of hospitalized kidney transplant recipients with COVID-19 infection in China during the Omicron wave:a single-center cohort study

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2024年第6期25卷 529-540页

作者： Duo LV Xishao XIE Qinyun YANG Zhimin CHEN Guangjun LIU Wenhan PENG Rending WANG Hongfeng HUANG Jianghua CHEN Jianyong WU Department of Clinical Pharmacy the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research Hangzhou 310003China Kidney Disease Center the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Key Laboratory of Kidney Disease Prevention and Control Technology Zhejiang ProvinceHangzhou 310003China Institute of Nephrology Zhejiang UniversityHangzhou 310003China Zhejiang Clinical Research Center of Kidney and Urinary System Disease Hangzhou 310003China The Third Grade Laboratory under the National State Administration of Traditional Chinese MedicineHangzhou 310003China Information Center the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China

Background:Following the short-term outbreak of coronavirus disease 2019(COVID-19)in December 2022 in China,clinical data on kidney transplant recipients(KTRs)with COVID-19 are ***:We conducted a single-center retrospective study to describe the clinical features,complications,and mortality rates of hospitalized KTRs infected with COVID-19 between Dec.16,2022 and Jan.31,*** patients were followed up until Mar.31,***:A total of 324 KTRs with COVID-19 were *** median age was 49 *** median time between the onset of symptoms and admission was 13 ***,azvudine,and nirmatrelvir/ritonavir were administered to 67(20.7%),11(3.4%),and 148(45.7%)patients,***-nine(9.0%)patients were treated with more than one antiviral ***-eight(14.8%)patients were treated with tocilizumab and 53(16.4%)patients received baricitinib *** acute kidney injury(AKI)occurred in 81(25.0%)patients and 39(12.0%)patients were admitted to intensive care *** infections were observed in 55(17.0%)***(15.4%)patients lost their *** 28-d mortality rate of patients was 9.0%and 42(13.0%)patients died by the end of *** Cox regression analysis identified that cerebrovascular disease,AKI incidence,interleukin(IL)-6 level of>6.8 pg/mL,daily dose of corticosteroids of>50 mg,and fungal infection were all associated with an increased risk of death for hospitalized ***:Our findings demonstrate that hospitalized KTRs with COVID-19 are at high risk of *** administration of immunomodulators or the late application of antiviral drugs does not improve patient survival,while higher doses of corticosteroids may increase the death risk.

关键词： Coronavirus disease 2019(COVID-19) Kidney transplant Hospitalization Mortality

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Performance Analysis of Phase Pre-Configured Spatial Modulation Empowered by RIS With Discrete Phase Alphabet

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chaowen Shi, Zhengmin Zheng, Tong-Xing Liu, Boyang Wen, Miaowen Wang, Wenjie Lu, Guangyue Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China National Key Laboratory of Multi-domain Data Collaborative Processing and Control Xi'an710068 China Xi'an Jiaotong University School of Information and Communications Engineering Xi'an710049 China South China University of Technology School of Electronics and Information Engineering Guangzhou510641 China

In this paper, we are motivated to introduce and investigate a novel reconfigurable intelligent surface assisted phase preconfigured spatial modulation (RIS-PPSM) scheme, which can be employed to achieve reliability enhanced transmissions. In the RIS-PPSM scheme, pre-configured phases are injected at the transmitter, and the reflection coefficients are designed for the RIS with a practical discrete phase alphabet, such that the resolution of transmit antennas is increased, and hence the overall transmission performance is remarkably elevated. Upon utilizing the moment generating function based unified analysis framework, we deduce out the closed-form expressions for the average bit error probability upper bound and discrete input continuous-output memoryless channel capacity. Finally, simulation results are depicted to demonstrate the accuracy of the theoretical analysis and the superiority of the proposed RIS-PPSM. © 1967-2012 IEEE.

关键词： discrete phase alphabet performance analysis phase pre-configuration Reconfigurable intelligent surface (RIS) spatial modulation

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Optimal Multi-Robot Path Planning for Cyclic Tasks using Petri Nets

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IFAC-PapersOnLine 2022年第28期55卷 9-15页

作者： Peng Lv Guangqing Luo Xiang Yin Ziyue Ma Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China School of Electro-Mechanical Engineering Xidian University Xi'an 710071 China

In this paper, we investigate the problem of optimal multi-robot path planning for a cyclic task represented by a particular type of linear-temporal logic (LTL) formulae. Specifically, the team of robot needs to fulfill a given LTL formula and at the same time, accomplishes some particular tasks infinitely often. To avoid the state-space explosion when the number of robot increases, we use Petri nets to model the team of multi-robot. Our goal is to find an optimal infinite sequence in the prefix-suffix form for each robot such that the average cost per task is minimized. We propose an efficient planning method based on the notion of basis reachability graph (BRG), which is a compact representation of the reachability space of the PN. We demonstrate the computational efficiency of our method through illustrative examples.

关键词： Petri Nets Linear Temporal Logic Multi-Robot systems Task Planning

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A Vector control-based Design of Multi-port Interline DC Power Flow controller for HVDC system

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Electric Power systems Research 2025年 248卷

作者： Khan, Muhammad Qasim Khan, Muhammad Mansoor Nawaz, Arshad Wang, Haibing Chengmin, Wang School of Electrical Engineering and Key Laboratory of Control of Power Transmission and Transformation Ministry of Education of China Shanghai Jiao Tong University Shanghai China School of Automation and Key Laboratory of System Control Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China University of Shanghai for Science and Technology Shanghai China

The Interline DC Power Flow controller (IDCPFC) represents a significant advancement in power distribution and control within Multi-Terminal High Voltage DC (MT-HVDC) systems. Traditional IDCPFC control without external voltage support suffers from coupling issues due to coupled dynamics, which limits transient response in multi-legged converter-based IDCPFC systems. This paper introduces a novel approach that employs vector-based decomposition to address this issue by decoupling current regulation from DC-link voltage regulation, thereby efficiently managing DC power flow across multiple transmission lines in the grid. Furthermore, the concept of zero-sequence control for IDCPFC is introduced. The incorporation of the zero-sequence algorithm increases modulation depth by up to 25%, enhancing DC link voltage utilization and improving system efficiency by reducing switching losses by up to 12%. The proposed method undergoes a detailed analysis encompassing network topology, operational principles, and decoupled control strategies. Simulations and experimental results validate the method's effectiveness under various grid scenarios. © 2025

关键词： Decouple control Interline DC Power Flow controller Multi-port HVDC Zero-sequence Algorithm

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Inferring DTIs Based on Similarity Clustering and CaGCN-DTI Model from Heterogeneous Network

Inferring DTIs Based on Similarity Clustering and CaGCN-DTI ...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Li, Aoxing Lin, Xiaoli Yu, Haiping Wuhan University of Science and Technology Hubei Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science and Technology Wuhan China Huanggang Normal University Hubei Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science Wuhan China

ISBN: (纸本)9781665401265

Although much progress has been made in new drug development, it is still a costly, complicated and less efficient process. Therefore, drug repositioning studies are highly desirable. So far, many methods based on known drug-target interactions (DTIs) have been designed to detect potential DTIs, but there are many challenges for improving the performance of prediction DTIs. This paper proposes a new method (CaGCN-DTI) for DTIs prediction, which uses a heterogeneous network that incorporates a wide variety of biological data (drug, target, disease, and side effect) to discover potential interactions between drugs and targets. First, the drug-protein similarity network is preprocessed by Spectral clustering, then the graph convolutional network (GCN) combined with attention mechanism and random walk with restart (RWR) is used to aggregate message transmission to the network. Finally, the embedding vectors are used to discover potential DTIs by matrix decomposition. Experiments are performed based on ten-fold cross-validation, and the results show that CaGCN-DTI outperforms other previous methods in terms of AUC and AUPR. © 2021 IEEE.

关键词： Convolution

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Source-free Unsupervised Domain Adaptation for Privacy-Preserving Intelligent Fault Diagnosis 3

Source-free Unsupervised Domain Adaptation for Privacy-Prese...

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3rd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Zhu, Mengliang Zeng, Xiangyu Liu, Jie Zhou, Kaibo MOE Key Laboratory of Image Information Processing and Intelligent Control School of Artificial Huazhong University of Science and Technology Wuhan China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665492812

Rolling bearing is of vital significance in industrial applications and Intelligent fault diagnosis (IFD) have been widely exploited in this field. However, cross-machine variations hinder the model performance across different machines in varying working conditions. To solve this issue, many unsupervised domain adaptation (UDA) approaches have been proposed recently, requiring direct access to the fully labeled source domain. However, privacy concerns are raised in traditional UDA scenario, since raw signals contain various private information. To address this issue, the source-free unsupervised domain adaptation (SFUDA) scenario is considered, where only the pre-trained source model is required, instead of the fully labeled source domain. In this paper, a SFUDA approach for intelligent fault diagnosis (IFD) is proposed. It consists of two steps: 1) source model generalization, where virtual adversarial training, R-Drop and label smoothing techniques are adopted to improve the generalization ability of the source model;and 2) target model adaptation, where information maximization is used for cluster assumption and mean teacher training paradigm is utilized to alleviate the catastrophic forgetting phenomenon. The proposed approach is verified on the Case Western Reserve University (CWRU) dataset. Experimental results on the show that the proposed SFUDA approach outperforms several typical UDA approaches, and its effectiveness is verified. © 2022 IEEE.

关键词： intelligent fault diagnosis privacy concerns Rolling bearing source-free unsupervised domain adaptation

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controller Design for Switched LPV systems with Hidden semi-Markov Mode Switching 11

Controller Design for Switched LPV Systems with Hidden semi-...

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11th International Conference on Intelligent control and information processing, ICICIP 2021

作者： Wang, Jianfeng Chen, Zhiru Sun, Yichong Li, Zhan Pei, Dacheng Cai, Bo China Institute of Marine Technology & Economy Beijing China Beijing Machine and Equipment Institute Beijing China Harbin Institute of Technology Key Laboratory of System Control and Information Processing Harbin China

ISBN: (纸本)9781665425155

This paper is concerned with issue of stability analysis and control synthesis for a class of switched LPV systems with stochastic mode switching. The stochastic switching process is further regarded as hidden semi-Markov switching by using concepts of semi-Markov kernel and emission probability. With the construction of a novel Lyapunov function that depends on accessible-mode, parameter as well as elapsed time, the mean-square stability (MSS) criteria are developed for the closed-loop system with the usage of designed controller. Numerically testable stability criteria are established in sense of MSS by introducing the upper bound sojourn time and some mathematical techniques. The theoretical results are testified by a numerical example to demonstrate the effectiveness of the designed stabilizing controller. © 2021 IEEE.

关键词： Stability criteria

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A detection method for granary storage states based on a support vector machine and domain knowledge

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Acta Agriculturae Scandinavica Section B: Soil and Plant Science 2021年第1期71卷 45-51页

作者： Zhang, Dexian Cheng, Cong Zhang, Miao College of Information Science and Engineering Henan University of Technology Zhengzhou China Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Zhengzhou China

Automatic detection of granary storage states is an important technology to ensure national food security. In view of distribution characteristics of bottom pressure, this study theoretically explored a relationship between detected value of bottom pressure of granaries and granary storage states through the technologies, such as integrated learning and nonlinear regression. On this basis, this research built layout models of single-ring pressure sensors on the bottom of granaries and proposed a detection method for granary storage states based on domain knowledge of statistics of bottom pressure in granaries. The experiment demonstrates that the detection method for granary storage states based on a support vector machine (SVM) and domain knowledge shows high detection accuracy and low requirements for sensor performance and low detection cost. Therefore, it can meet the needs of remote online detection of granary storage states usually used. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： detection accuracy Detection of granary storage state domain knowledge food security support vector machine

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Scene Classification Using Deep Networks Combined with Visual Attention

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Journal of Sensors 2022年第0期2022卷

作者： Shi, Jing Zhu, Hong Li, Yuxing Li, Yanghui Du, Sen School of Automation and Information Engineering Xi'An University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an710048 China

In view of the scene's complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability. © 2022 Jing Shi et al.

关键词： Convolution

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