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Solo Adaptation for Distributed Synchronization With Application to Event-Triggered Linear Multi-Agent Systems

IEEE Transactions on Automatic control 2025年第6期70卷 4225-4232页

作者： Chen, Ci Zheng, Zhiyang Lewis, Frank L. Xie, Kan Xie, Shengli Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education School of Automation Guangzhou510006 China Guangdong University of Technology School of Automation Guangdong Guangzhou510006 China The University of Texas at Arlington UTA Research Institute Fort Worth76118 United States Guangdong University of Technology 111 Center for Intelligent Batch Manufacturing Based on IoT Technology School of Automation Guangzhou China Guangdong University of Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of Education School of Automation Guangzhou510006 China

We study a solo adaptation-based protocol design problem for distributed synchronization of event-triggered linear multi-agent systems (MAS) over general directed graphs. We show that a solo adaptive gain, a locally static control gain matrix, and a distributed state measurement are sufficient for obtaining adaptive distributed synchronization of linear MAS over directed graphs without any prior knowledge of the global communication network. We then extend the solo adaptation structure to formulate an event-triggered synchronization control protocol. The main feature of our result is that the time for triggering a subsequent event is now computed using the distributed event-triggered state measurement, rather than the continuous-time state measurement. © 1963-2012 IEEE.

关键词： Continuous time systems

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Event-Triggered Optimal Nonlinear Systems control Based on State Observer and Neural Network

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Journal of Systems Science & Complexity 2023年第1期36卷 222-238页

作者： CHENG Songsong LI Haoyun GUO Yuchao PAN Tianhong FAN Yuan Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China

This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation ***,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation ***,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno ***,the authors provide a numerical example to illustrate the effectiveness of the proposed method.

关键词： Event-triggered control neural network optimal control state observer

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BeltLineNet: A Shape-Prior-Guided Lightweight Network for Real-Time Deviation Detection in Circular Pipe Conveyors

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IEEE Sensors Journal 2025年第11期25卷 20024-20036页

作者： Zhao, Long Su, Jinhui Zhong, Yusheng Xie, Weiwei Su, Jinya Chen, Xisong Chen, Congyan Li, Shihua Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Fujian Longking Intelligent Conveying Engineering Co. Ltd Longyan China

Belt deviation in circular pipe conveyor systems could lead to material spillage, environmental contamination, reduced efficiency, and accelerated belt wear. Real-time belt deviation detection is crucial for ensuring safe and efficient operation. However, existing methods, primarily developed for flat-belt systems, heavily rely on distinct belt-background semantics, making them unsuitable for circular conveyors where indistinct target features, motion blur, and occlusions pose significant challenges. To address these issues, we reformulate the deviation detection task as an object detection problem, proposing BeltLineNet, a lightweight, real-time deviation detection network specifically designed for circular pipe conveyors. Our method integrates explicit feature learning with a coarse-to-fine global feature fusion mechanism, enhancing belt line representation under complex conditions. Additionally, a shape-prior loss strategy is introduced to improve supervision during training, ensuring more accurate detection of elongated targets. The model is also optimized for real-time deployment through layer-adaptive pruning, achieving a balance between accuracy and computational efficiency. Extensive comparative experiments involving 8 state-of-the-art (SOTA) feature extraction networks and 6 feature enhancement strategies on a self-collected dataset under industrial conditions demonstrate that BeltLineNet surpasses SOTA feature extraction and fusion networks, improving average precision (AP) by 8.23% before pruning and 6.33% after pruning. © 2001-2012 IEEE.

关键词： Belt conveyors

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Dual Averaging for Distributed Unbalanced Optimization with Delayed Information

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IEEE Transactions on Signal and Information Processing over Networks 2025年 11卷 366-377页

作者： Huang, Qing Fan, Yuan Cheng, Songsong Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui Hefei230601 China

In this paper, we study a category of distributed constrained optimization problems where each agent has access to local information, communicates with its neighbors, and cooperatively minimizes the aggregated cost functions over time-varying unbalanced graphs. To address the considered problems, we propose a distributed dual averaging algorithm based on a row-stochastic weighted matrix (DDAR), which improves the robustness of network topology compared to conventional push-sum algorithms. Moreover, we develop a modified version of DDAR with delayed information (DDARD), which considers the delays of both network communication and gradient calculation, enhancing the algorithm's flexibility in communication and iteration. Our analysis demonstrates that the DDAR and DDARD achieve the optimal value at rates of O(N/(1-λ)√T) and O(τ2N/(1-λ}})√T}), respectively. Finally, the theoretical results are confirmed by simulation on a logistic regression problem. © 2015 IEEE.

关键词： Cost functions

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Multi-stage Provincial Power Expansion Planning and Multi-market Trading Equilibrium

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1652-1665页

作者： Guangsheng Pan Zhongfan Gu Yuanyuan Sun Kaiqi Sun Wei Gu the School of Electrical Engineering Southeast UniversityNanjingChina Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical EngineeringShandong UniversityJinanChina

Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality,and the top-level design needs to be carried out from the perspective of power planning.A multi-stage provincial power expansion planning(PPEP)model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy *** model covers 16 types of power supply,considering macro-policy demands and micro-operation *** stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone ***,the soft dynamic time warping(soft-DTW)based K-medoids technique is adopted to generate typical scenarios for balancing the model accuracy and solution ***,a multi-market trading equilibrium(MMTE)mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service *** the coalbased units take on the task of providing ancillary services from renewable-based units in the ancillary service market,the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them,thus improving the motivation of coal-based units.A case study in Xinjiang province,China,verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.

关键词： Power expansion planning market design ancillary service market renewable energy generation energy market

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Event-triggered predefined-time control for full-state constrained nonlinear systems: A novel command filtering error compensation method

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Science China(Technological Sciences) 2024年第9期67卷 2867-2880页

作者： PAN YingNan CHEN YiLin LIANG HongJing College of Control Science and Engineering Bohai UniversityJinzhou 121013China School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China

In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sliding mode differentiator, the inherent computational complexity problem within the predefined-time backstepping framework is solved. Different from the existing command filter-based finite-time and fixed-time control strategies that the convergence time of the filtering error is adjusted through the system initial value or numerous parameters, a novel command filtering error compensation method is presented,which tunes one control parameter to make the filtering error converge in the predefined time, thereby reducing the complexity of design and analysis of processing the filtering error. Then, an improved event-triggered mechanism(ETM) that builds upon the switching threshold strategy, in which an inverse cotangent function is designed to replace the residual term of the ETM,is proposed to gradually release the controller's dependence on the residual term with increasing time. Furthermore, a tan-type nonlinear mapping technique is applied to tackle the time-varying full-state constraints problem. By the predefined-time stability theory, all signals in the uncertain nonlinear systems exhibit predefined-time stability. Finally, the feasibility of the proposed algorithm is substantiated through two simulation results.

关键词： predefined-time control command filtering error compensation method event-triggered mechanism time-varying full-state constraints uncertain nonlinear systems

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Micromechanical characterization of microwave dielectric ceramic BaO-Sm_(2)O_(3)-5TiO_(2),by indentation and scratch methods

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Journal of Advanced Ceramics 2023年第6期12卷 1136-1165页

作者： Ming Liu Zhitong Xu Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhou 350108China

Mechanical characterization of dielectric ceramics,which have drawn extensive attention in wireless communication,remains *** micromechanical properties with the microstructures of dielectric ceramic BaO-Sm_(2)O_(3)-5TiO_(2)(BST)were assessed by nanoindentation,microhardness,and microscratch tests under different indenters,along with the X-ray diffraction(XRD),scanning electron microscopy(SEM),and Raman *** determination of elastic modulus(Err)(i.e.,260 GPa)and indentation hardness(Hrr)(i.e.,16.2 GPa)of brittle BST ceramic by the instrumented indentation technique requires low loads with little indentation-induced *** elastic modulus and indentation hardness were analyzed by different methodologies such as energy-based approach,displacement-based approach,and elastic recovery of Knoop *** values(about 3.1 MPa·m^(1/2))of fracture toughness(Kc)of BST ceramic were obtained by different methods such as the Vickers indenter-induced cracking method,energy-based nanoindentation approaches,and linear elastic fracture mechanics(LEFM)-based scratch approach with a spherical indenter,demonstrating successful applications of indentation and scratch methods in characterizing fracture properties of brittle *** deterioration of elastic modulus or indentation hardness with the increase in indentation load(F)is caused by indentation-induced damage and can be used to determine the fracture toughness of material by energy-based nanoindentation approaches,and the critical void volume fraction(f^(*))is 0.27(or 0.18)if elastic modulus(or indentation hardness)of the brittle BST ceramic is *** fracture work at the critical load corresponding to the initial decrease in elastic modulus or indentation hardness can also be used to assess the fracture toughness of brittle solids,opening new venues of the application of nanoindentation test as a means to characterize the fracture toughness of brittle ceramics.

关键词： brittle ceramics micromechanical properties instrumented indentation microscratch fracture toughness(K_(c)) grid nanoindentation

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Fault diagnosis of rolling bearings with noise signal based on modified kernel principal component analysis and DC‐ResNet

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1014-1028页

作者： Yunji Zhao Menglin Zhou Xiaozhuo Xu Nannan Zhang School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuoChina Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Henan Polytechnic UniversityJiaozuoChina

In view of the influence of aliasing noise on the effectiveness and accuracy of bearing fault diagnosis,a bearing fault diagnosis algorithm based on the spatial decoupling method of modified kernel principal component analysis(MKPCA)and the residual network with deformable convolution(DC‐ResNet)is innovatively ***,the Gaussian noise with different signal‐to‐noise ratios(SNRs)is added to the data to simulate the different degrees of noise in the actual data acquisition *** MKPCA is used to project the fault signal with different SNRs in the kernel space to reduce the data dimension and eliminate some noise ***,the DC‐ResNet model is used to further filter the noise effects and fully extract the fault features through the training of the preprocessed *** proposed algorithm is tested on the Case Western Reserve University(CWRU)and Xi'an Jiaotong University and Changxing Sumyoung Technology Co.,Ltd.(XJTU‐SY)bearing data sets with different SNR *** fault diagnosis accuracy can reach 100%within 30 min,which has better performance than most of the existing *** experimental results show that the algorithm has an excellent effect on accuracy and computation complexity under different noise levels.

关键词： artificial intelligence classification deep learning fault feature extraction

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An improved high-fidelity adaptive model for integrated inlet-engine-nozzle based on mechanismdata fusion

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Chinese Journal of Aeronautics 2024年第8期37卷 190-207页

作者： Chen WANG Ziyang YU Xian DU Ximing SUN School of Control Science and Engineering Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of EducationDalian University of TechnologyDalian 116024China

Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion *** component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model,failing to meet the accuracy requirements of supersonic *** paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental ***,a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm(SSA-ELM)is *** study reveals the inlet model’s efficacy in reflecting installed performance,flow matching,and mitigating pressure distortion,while the nozzle model accurately predicts flow coefficients and thrust coefficients,and identifies various operational *** model’s output closely aligns with typical experimental *** combining offline optimization and online adaptive correction,the mechanismdata fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation,and effectively handles gradual degradation within a single flight ***,the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location *** approach significantly curbs performance deviations in supersonic *** example,at Ma=2.0,the system error impressively drops from 34.17%to merely 6.54%,while errors for other flight conditions consistently stay below the 2.95%*** findings underscore the clear superiority of the proposed method.

关键词： Aero-propulsion system Integrated inlet-enginenozzle Component-level model On-board adaptive model Mechanism-data fusion Extreme learning machine

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Aeroengine thrust estimation and embedded verification based on improved temporal convolutional network

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Chinese Journal of Aeronautics 2024年第1期37卷 106-117页

作者： Wanzhi MENG Zhuorui PAN Sixin WEN Pan QIN Ximing SUN Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of TechnologyDalian 116024China School of Control Science and Engineering Dalian University of TechnologyDalian 116024China

Thrust estimation is a significant part of aeroengine thrust control *** traditional estimation methods are either low in accuracy or large in *** further improve the estimation effect,a thrust estimator based on Multi-layer Residual Temporal Convolutional Network(M-RTCN)is *** solve the problem of dead Rectified Linear Unit(ReLU),the proposed method uses the Gaussian Error Linear Unit(GELU)activation function instead of ReLU in residual *** the overall architecture of the multi-layer convolutional network is adjusted by using residual connections,so that the network thrust estimation effect and memory consumption are further ***,the comparison with seven other methods shows that the proposed method has the advantages of higher estimation accuracy and faster convergence ***,six neural network models are deployed in the embedded controller of the micro-turbojet *** Hardware-in-the-Loop(HIL)testing results demonstrate the superiority of M-RTCN in terms of estimation accuracy,memory occupation and running ***,an ignition verification is conducted to confirm the expected thrust estimation and real-time performance.

关键词： Thrust estimation Temporal convolutional network Embedded deployment Hardware-in-the-loop testing Ignition verification

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