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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2023

作者： Liu, Xuelin Wang, Weimin Liu, Zhixin School of Control Science and Engineering Dalian University of Technology Dalian116023 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Hebei Province Qinhuangdao066004 China

ISBN: (纸本)9798350315196

Femtocell network has a great development space in increasing coverage and capacity of wireless network. In order to meet the quality of service (QoS) requirements of MUEs in MBS coverage, we propose a seed channel incentive mechanism in the two-tier femtocell network, where the MBS provides sub-channels to FBSs to motivate them to serve for the MUEs within the MBS coverage. To maximize the energy efficiency of femtocell layer after hybrid access, the optimization problem is modeled. The combined method of worst-case, Dinkelbach and continuous convex approximation is developed to make the optimization problem solvable. In addition, in order to realize the practical application of the proposed scheme, an optimization algorithm combining sub-channel and power allocation is developed. The numerical results show that the proposed algorithm is effective in improving the energy efficiency of the femtocell layer. © 2023 IEEE.

关键词： Femtocell

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Fully Distributed Adaptive Finite Time Fault-Tolerant control for Multi-Agent Systems with Actuator Faults

Fully Distributed Adaptive Finite Time Fault-Tolerant Contro...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Xiaoqi Wang Yiming Fang Miao Xu Zhichao Lei Key Labpratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei Province China Engineering Research Center of the Education Ministry for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao Hebei Province China

For a class of second-order nonlinear leader-following multi-agent systems with actuator faults and integral quadratic constraints (IQCs) of followers, a fully distributed adaptive consensus control algorithm based on improved PID sliding mode is designed. The algorithm only requires local topology information but no global information. According to Lyapunov stability theory, it is demonstrated that multi-agent systems can converge to the vicinity near equilibrium points within a finite time. Finally, the feasibility of the control algorithm proposed in this paper is verified by numerical simulation of multi-agent systems.

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Event-Triggered-Based Robust control of Heterogeneous Connected Vehicles Platoon with Communication Delay and Random Packet Loss 8

Event-Triggered-Based Robust Control of Heterogeneous Connec...

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8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Liu, Chen Ru, Shuangkun Qi, Lin Fang, Jiayi Zhang, Ting Yanshan University Hebei Key Laboratory of Industrial Computer Control Engineering Hebei Province Qinhuangdao066004 China School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Vehicle and Mobility Tsinghua University Beijing100081 China

ISBN: (纸本)9798331504892

With the development of vehicle autonomous driving technology and wireless network communication technology, the mix platoon of connected autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs) is becoming inevitable. The abnormal V2V communication and uncertain vehicle dynamics may affect the CAV control performance. Considering time-varying communication delays and random packet loss, an event-trigger-based robust control strategy is proposed based on the stability theory of stochastic time-delay systems. The Bernoulli packet loss model is constructed to solve the random packet loss problem. The robust controller with the event-triggered mechanism designed using the Lyapunov functional stability theory of stochastic systems ensures the stability of the mix platoon with vehicle heterogeneity and the stability of CAV. The simulation comparison has verified that the proposed control strategy can better suppress the fluctuation of the preceding vehicle and more quickly reach the desired value when both time delay and packet loss are present. © 2024 IEEE.

关键词： Stochastic systems

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Design and Analysis of Polynomial Positive Fuzzy System controllers Based on Markov Transitions

Design and Analysis of Polynomial Positive Fuzzy System Cont...

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Chinese Automation Congress (CAC)

作者： Sen Chang Xiaomiao Li Fucai Liu Zhiyong Bao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

This study explores polynomial Markov positive fuzzy systems, formulating controllers for these systems by examining the prerequisites for positivity and stochastic stability. Initially, polynomials are incorporated into the Markov positive fuzzy system to represent nonlinear elements better and enhance its capacity to model nonlinear systems. Concurrently, the study discusses the non-convex scenarios encountered in the stability analysis of the closed-loop system once the positive fuzzy system controller is integrated and confirms the stability of the Markov polynomial positive fuzzy system. Ultimately, the effectiveness of the proposed approaches is demonstrated through a numerical simulation example.

关键词： Automation Stochastic processes Numerical simulation Stability analysis Polynomials Numerical models Closed loop systems Nonlinear systems Numerical stability Fuzzy systems

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Immoral post detection using a one-dimensional convolutional neural network-based LSTM network

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Multimedia Tools and Applications 2025年 1-20页

作者： Saqia, Bibi Khan, Khairullah Rahman, Atta Ur Khan, Aurangzeb Jain, Deepak Kumar Department of Computer Science University of Science and Technology Bannu28100 Pakistan Riphah Institute of Systems Engineering Riphah International University Islamabad46000 Pakistan Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China Symbiosis Institute of Technology Symbiosis International University Pune India

In text mining and Natural Language Processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has compelled the advancement of more sophisticated methods for the automatic identification of unwanted content. The One-Dimensional Convolutional Neural Network (1D-CNN) performs best for feature extraction, while the Long Short-Term Memory Network (LSTM) is well-known for extracting sequential features and classification of textual data. This study proposes a novel solution by combining 1D-CNN with LSTM. Utilizing a context-aware model, this study aims to enhance the detection of immoral posts, including hate speech and other forms of immoral content on social media platforms. Various posts are extracted from social media, which are then processed using Glove word embedding models. It depicts the word representations in the text, which yields the form of a real-valued vector determining the words' meaning. The 1D convolution utilizes a filter window over the input time-series data to extract features. Relying on the acquired parameters of the filters, they act as feature extractors. This feature extraction technique allows the model to distinguish detailed patterns and nuances from the textual contents of posts. The sequential processing capabilities of the LSTM network enable an in-depth examination of the text, capturing temporal relationships and context, which is critical for successful content categorization. To validate the proposed model, we utilized a benchmark dataset, called the Twitter dataset. The proposed model achieved the highest accuracy of 95.37% and outperforms state-of-the-art works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Drosophila Larvae-Inspired Soft Crawling Robot with Multimodal Locomotion and Versatile Applications

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Research 2025年第1期7卷 35-46页

作者： Qin Fang Jingyu Zhang Yinhui He Nenggan Zheng Yue Wang Rong Xiong Zhefeng Gong Haojian Lu State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Institute of Cyber-Systems and Control Zhejiang UniversityHangzhou 310027China Medical School of Zhejiang University Hangzhou 310027China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Stomatology Hospital School of StomatologyZhejiang University School of MedicineZhejiang Provincial Clinical Research Center for Oral DiseasesKey Laboratory of Oral Biomedical Research of Zhejiang ProvinceCancer Center of Zhejiang UniversityEngineering Research Center of Oral Biomaterials and Devices of Zhejiang ProvinceHangzhou 310000China

Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible ***,most existing soft crawling robots typically exhibit a single-motion mode and lack diverse *** by Drosophila larvae,this paper proposes a compact soft crawling robot(weight,13 g;length,165 mm;diameter,35 mm)with multimodal locomotion(forward,turning,rolling,and twisting).Each robot module uses 4 sets of high-power-density shape memory alloy actuators,endowing it with 4 degrees of motion *** analyze the mechanical characteristics of the robot modules through experiments and simulation *** plug-and-play modules can be quickly assembled to meet different motion and task *** soft crawling robot can be remotely operated with an external controller,showcasing multimodal motion on various material *** a narrow maze,the robot demonstrates agile movement and effective maneuvering around *** addition,leveraging the inherent bistable characteristics of the robot modules,we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline *** robot completed the inspection in horizontal,vertical,curved,and branched pipelines,adjusted the camera view,and twisted a valve in the pipeline for the first *** research highlights the robot's superior locomotion and application capabilities,providing an innovative strategy for the development of lightweight,compact,and multifunctional soft crawling robots.

关键词： multimodal locomotion versatile applications Drosophila larvae soft crawling robot weight soft crawling robots shape memory alloy actuators

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Data-Driven Active Power Dispatch for Wind Farms 13

Data-Driven Active Power Dispatch for Wind Farms

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Jiao, Xuguo Zhang, Daoyuan Wang, Xin Ma, Zhaoxing Zhang, Zhenyong Liu, Wenfeng School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China School of Civil Engineering Qingdao University of Technology Qingdao266520 China

ISBN: (纸本)9798350361674

Active power dispatch of wind farms plays an important role in power grid scheduling. In this paper, a data-driven active power dispatch strategy for wind farms is proposed, which uses the key point of minimizing the standard deviation of wind turbines' output power series to reduce their fluctuations. First, to build the optimization problem, the historical active power output data of each wind turbine is collected from the Supervisory control And Data Acquisition (SCADA) system. Then, the objective function is developed based on the idea of minimizing the standard deviation of the output power time series. Meanwhile, considering the constraints of wind turbines' output power and active power balance of the grid, the feasible domain of the cost function is constructed. Further, to solve the proposed nonlinear optimization problem with equality and inequality constraints, the trust region interior point method (TRIPM) is employed to explore optimal solution within the feasible domain. Finally, actual data collected from wind farms is used to test effectiveness of the designed approach and experimental results show that our method can achieve better output power smoothing performance than conventional Proportional Dispatch (PD) method. © 2024 IEEE.

关键词： Cost functions

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Face Inpainting Based on Gan Multi-Dimensional Consistency Guidance

SSRN

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SSRN 2024年

作者： Li, Yaqian Zhan, Xin Li, Haibin Zhang, Wenming Hebei Provincial Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao066004 China

A B S T R A C TThe averageness of low-frequency features and the unreliability of high-frequency features result in identity deviations in the inpainted faces. To address this problem, a two-stage generative model is proposed, which includes structural prior guidance and multidimensional consistency guidance. Firstly, a parsing inpainting module was designed to predict structural information. Subsequently, a multidimensional information guidance module was constructed, which, based on semantic consistency guidance, extracts low-frequency confidence information of the inpainted image to suppress the averageness of facial inpainting. Frequency-domain information is extracted from the inpainted image, combined with a facial recognition network, and the frequency-domain identity feature consistency loss is calculated to aid in the inpainting of high-frequency information, including identity features, thus achieving identity consistency in facial inpainting. © 2024, The Authors. All rights reserved.

关键词： Face recognition

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Distributed Resilient Frequency control Based on Estimation of Sensor and Actuator Attacks in AC Microgrids 48

Distributed Resilient Frequency Control Based on Estimation ...

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48th Annual Conference of the IEEE industrial Electronics Society, IECON 2022

作者： Ma, Kai Dong, Yufei Zhao, Peng Yang, Jie Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao China Yanshan University School of Electrical Engineering Qinhuangdao China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

The consensus based distributed frequency control strategy makes all measurements and control units in microgrids vulnerable to false data injection (FDI) attacks. This paper presents an observer-based resilient frequency control for estimating and compensating for FDI attacks on sensors and actuators in AC microgrids. Firstly, attacks of sensors and actuators are estimated online simultaneously by observers. Then a distributed H∞ output feedback protocol is used to ensure that the frequency consensus tracking is achieved with cooperative uniform ultimate boundedness. The control strategy is completely distributed and does not require any quantitative information about attacks. Furthermore, there is no limit to the number and location of attacked units. Several case studies are provided to verify the effectiveness of the proposed resilient frequency control strategy. © 2022 IEEE.

关键词： Frequency estimation

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Semi-Cervixseg: A Multi-Stage Training Strategy for Semi-Supervised Cervical Segmentation 22

Semi-Cervixseg: A Multi-Stage Training Strategy for Semi-Sup...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Jiang, Juntao Bi, Yali Zhou, Chunlin Liu, Yong Zhang, Jiangning College of Computer and Information Science Southwest University United States College of Control Science and Engineering Zhejiang University China Zhejiang University State Key Laboratory of Industrial Control Technology China Youtu Lab Tencent China

ISBN: (纸本)9798331520526

Image segmentation plays a critical role in computer-aided diagnosis and treatment planning for cervical cancer. Obtaining a large number of labeled images for supervised cervical segmentation is often labor-intensive and time-consuming. In this paper, we propose a multi-stage semi-supervised learning framework (Semi-CervixSeg) to address the cervical seg-mentation task in ultrasound images for Fetal Ultrasound Grand Challenge: Semi-Supervised Cervical Segmentation in ISBI 2025. Specifically, in the initial stage, we utilize unlabeled data through a multi-view random augmentation strategy, using consistency constraints and a contrastive learning method. Subsequently, a progressive multi-stage training strategy is adopted to generate and optimize pseudo-labels, further improving segmentation results. Experimental re-sults demonstrate that the proposed method significantly im-proves segmentation performance compared with supervised methods. As a technical report for the challenge, this paper elaborates on our methodology and experimental findings in detail. The code can be accessed at h t t p s: / / g i t hub. com/juntaoJianggavin/Semi-CervixSeg. © 2025 IEEE.

关键词： Semi-supervised learning

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