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Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties:Fundamental Variance Bounds

Journal of Systems Science & Complexity 2021年第5期34卷 1858-1878页

作者： QI Tian CHEN Jie School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked ControlSouth China University of TechnologyGuangzhou 510640China Department of Electrical Engineering City University of Hong KongHong KongChina

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative *** authors consider multi-input,multi-output(MIMO)linear time-invariant systems subject to multiple static,structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square *** the stochastic control framework,this problem can be considered as one of optimal control under state-or input-dependent random noises,while in the networked control setting,a problem of networked feedback stabilization over lossy communication *** authors adopt a mean-square small gain analysis approach,and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output *** single-input,single-output(SISO)systems,the condition provides an analytical bound,demonstrating explicitly how plant unstable poles,nonminimum phase zeros,and time delay may impose a limit on the uncertainty variance required for mean-square *** MIMO minimum phase systems with possible delays,the condition amounts to solving a generalized eigenvalue problem,readily solvable using linear matrix inequality optimization techniques.

关键词： Mean-square small gain theorem multiplicative stochastic uncertainty networked control

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Finite element joint simulation model applied to fast mechanical switching of controlled resonance combination circuit breakers

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High Voltage 2025年第2期10卷 419-435页

作者： Puyi Cui Guoli Li Zehui Sun Jiazi Xu Guoyong Zhang Zhong Chen Weiping Guan School of Electrical Engineering and Automation Anhui UniversityHefeiChina Engineering Research Center of Power Quality Ministry of EducationAnhui UniversityHefeiChina Anhui Key Laboratory of Industrial Energy-Saving and Safety Anhui UniversityHefeiChina Anhui Collaborative Innovation Center of Industrial Energy-Saving and Power Quality Control Anhui UniversityHefeiChina Anhui Zhengguangdian Electric Power Technology Co. HefeiChina Electric Power Research Institute of State Grid Anhui Electric Power Co. Ltd.HefeiChina

Fast mechanical switches(FMSs)are critical components of DC circuit breakers(DCCBs),which require the switch action time to break to a sufficient distance within 3 ms in the DC line breaking scenario,while ensuring a long service *** breaking mechanism significantly affects the current interruption capability of *** operation of the repulsion mechanism,along with the morphology of the arc and its transformation within the interrupter chamber,collectively influence the breaking performance of the *** paper presents a comprehensive analysis of the FMSs,which serves as the pivotal component of controlled resonance combination circuit breakers(CRCBs).This study establishes a multi physics coupling simulation analysis method based on the equivalent circuit of repulsion mechanism discharge,combined with electromagnetic and solid mechanics *** constructing a full cycle magnetohydrodynamic particle arc(MHP)model and using a combined simulation of Finite Element joint model(FEJM),the evolution law of arc characteristics during the superimposed current interruption process was systematically *** focus was on analysing the physical process of the zero zone of the superimposed arc,the multi physics field coupling relationship of the arc,and the interaction mechanism with external characteristic *** combining with optimisation design methods,the effectiveness of the model was verified through experiments,FEJM provides comprehensive technical support for effectively reflecting the stress issues of core components during the breaking process of FMS and can provide accurate theoretical references for the optimisation design of mechanical motion components in *** also accurately represents the arc extinguishing process during the breaking of FMS and provides a convenient method for the selection and design of circuit parameters for the entire circuit breaker.

关键词： dc circuit breakers dccbs which interrupter chambercollectively dc line breaking repulsion mechanismalong fast mechanical switching breaking mechanism fast mechanical switches fmss finite element joint simulation model

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Fuzzy-Cycle: Visible to Infrared Ship Image Translation Based on CycleGAN 6

Fuzzy-Cycle: Visible to Infrared Ship Image Translation Base...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： He, Long Yu, Yue Liu, Chang Sun, Yangyang Jiang, Feng Hu, Xiaoning Pan, Chengwei Dong, Xiwang School of Artificial Intelli-gence Beihang University Beijing China Beijing Institute of Control and Electronic Technology Beijing China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University School of Artificial Intelligence Institute of Unmanned System Beijing China

ISBN: (纸本)9798350356618

Detecting targets in infrared ship images is crucial for various applications, such as maritime rescue and ship inspection. Training contemporary mainstream detection and segmentation models, however, requires large-scale, high-quality infrared ship image datasets. In open-world maritime confrontation scenarios, the complex and variable environment, scarcity of target ships, and limited acquisition conditions make it challenging to construct high-quality infrared ship image datasets. To address this issue, this paper proposes an unpaired visible-infrared ship image translation model based on CycleGAN, named Fuzzy-Cycle. The model introduces a fuzzy cycle loss to encourage the model to learn feature mapping rules between different domains while minimizing attention to unnecessary features. Additionally, the method employs U-Net as the generator network to retain shallow image features during upsampling and selects PatchGAN as the discriminator network, embedding Haar wavelet transform to enhance the discriminator's ability to analyze image frequency domain features. Experiments on the VAIS dataset demonstrate that the proposed algorithm outperforms mainstream unpaired image transfer models, showing excellent performance in the task of visible-infrared ship image translation. Furthermore, zero-shot image translation experiments on the HRSC2016 dataset prove the generalizability and reliability of the proposed method. © 2024 IEEE.

关键词： Wavelet transforms

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Fault Diagnosis of Quadrotor UAV Propeller with Local-Global Attention-Based Graph Neural Networks 13

Fault Diagnosis of Quadrotor UAV Propeller with Local-Global...

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

作者： Wang, Zhiwei Liang, Shaojun Sun, Ye Yang, Yi Wang, Yanwei Zheng, Ying School of Artificial Intelligence and Automation Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China School of Ordnance Sergeant Army Engineering University Wuhan430075 China School of Mechanical & Electrical Engineering Wuhan Institute of Technology Wuhan430073 China

ISBN: (纸本)9798350361674

With the wide application of Quadrotor Unmanned Aerial Vehicles (QUAV) in military and civilian fields, its flight reliability problem has become a hot research topic. The propellers, which are the important components relating to the performance of QUAV, play a central role in safe flight. Traditional data-driven fault diagnosis methods of QUAV are based on Euclidean distance, which cannot effectively capture the interrelationship of multiple variables. In this paper, we treat the fault diagnosis of QUAV propeller as a node classification problem in non-Euclidean infinite dimensional space by introducing the method of Local-Global Attention-based Graph Neural Network (LGA-GNN). First, the graph topology is constructed using the KNN method based on the real flight log of the QUAV. Then, the local and global attention strategies are integrated to form a graph-based collaborative feature extraction model. Finally, a unified end-to-end fault diagnosis framework tailored for QUAV is proposed. In the experiment section, real flight data of QUAV with different propeller fault conditions are collected, and the effectiveness and superiority of the proposed method are verified by comparing with other methods based on real data. © 2024 IEEE.

关键词： Graph neural networks

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On a novel tracking differentiator design based on iterative learning in a moving window

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control Theory and Technology 2023年第1期21卷 46-55页

作者： Xiangyang Li Rafal Madonski Zhiqiang Gao Senping Tian Key Laboratory of Autonomous Systems and Network Control Ministry of EducationSchool of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510641China Energy and Electricity Research Center Jinan UniversityZhuhai 519070China Department of Electrical and Computer Science Cleveland State UniversityClevelandOH 44115USA

Differential signals are key in control engineering as they anticipate future behavior of process variables and therefore are critical in formulating control laws such as proportional-integral-derivative(PID).The practical challenge,however,is to extract such signals from noisy measurements and this difficulty is addressed first by *** in the form of linear and nonlinear tracking differentiator(TD).While improvements were made,TD did not completely resolve the conflict between the noise sensitivity and the accuracy and timeliness of the *** two approaches proposed in this paper start with the basic linear TD,but apply iterative learning mechanism to the historical data in a moving window(MW),to form two new iterative learning tracking differentiators(IL-TD):one is a parallel IL-TD using an iterative ladder network structure which is implementable in analog circuits;the other a serial IL-TD which is implementable digitally on any computer *** algorithms are validated in simulations which show that the proposed two IL-TDs have better tracking differentiation and de-noise performance compared to the existing linear TD.

关键词： Tracking differentiator(TD) Iterative learning Iterative learning tracking differentiator(IL-TD) Active disturbance rejection control(ADRC)-Two-dimensional system(2-D system)

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Consensus-Based Aggregation control and Formation Tracking control for Fixed-Wing UAV Swarm System 7th

Consensus-Based Aggregation Control and Formation Tracking ...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Hao, Ze Yu, Jianglong Chen, Yang Hu, Yangxiu Dong, Xiwang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shanghai Academy of Spaceflight Technology Shanghai201109 China

ISBN: (纸本)9789819733279

This paper investigates the problem of aggregation control and robust formation tracking control for the fixed-wing UAV swarm system after aggregation. Firstly, the dynamic models for aggregation control and formation tracking control of the fixed-wing UAV swarm system are established. Secondly, to solve the problem of large initial takeoff position deviation for multiple unmanned aerial vehicles, a consensus-based aggregation control algorithm is designed to converge the UAV swarm system to any position on a hovering circle to provide proper initial conditions for subsequent tasks. Thirdly, in the formation tracking control process, a nonlinear path tracking control algorithm is employed for leader UAV, and a formation tracking control algorithm based on leader-following navigation is designed for follower UAV swarm system. Finally, simulation results demonstrate that the proposed aggregation control algorithm enables rapid convergence of the UAV swarm system’s initial positions, and the designed formation tracking control achieves algorithm achieves fine formation tracking performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned aerial vehicles (UAV)

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries 13

Exponential Weighted Moving Average-Based Variational Mode D...

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

作者： Wu, Penghao Tao, Hongfeng Tian, Engang Yin, Tangwen Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350361674

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods. © 2024 IEEE.

关键词： Variational mode decomposition

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FRNet: A Full-Resolution Convolutional Neural Network for OCTA Vascular Segmentation 30

FRNet: A Full-Resolution Convolutional Neural Network for OC...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Wang, Liang Gao, Dongxu Gao, Hongwei Jiang, Guozhang Ju, Zhaojie Shenyang Ligong University School of Automation and Electrical Engineering Shenyang China University of Portsmouth School of Computing United Kingdom Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan China

ISBN: (纸本)9798350391916

Optical coherence tomography angiography (OCTA) is an advanced, non-invasive imaging technique. Automatic segmentation of vascular networks in retinal OCTA images is essential for the early diagnosis and progression assessment of various vision-related diseases. However, most existing methods for OCTA image vessel segmentation rely on encoder-decoder architectures, which typically involve a high number of parameters and result in slower inference speeds. In this paper, we introduce FRNet V2, an accurate and efficient neural network specifically designed for retinal vessel segmentation in OCTA images. This is achieved by integrating a modified recursive ConvNeXt V2 block and a recursive HAAM attention mechanism into a full-resolution convolutional network framework. We evaluate our proposed method on two large public datasets: ROSSA and OCTA-500. Experimental results demonstrate that our network achieves performance on par with other methods, while boasting significantly fewer parameters and faster inference speeds. This makes it highly suitable for practical industrial applications. © 2024 IEEE.

关键词： Optical coherence tomography

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Path Optimization Study of Military Material Based on Time Uncertainty 2

Path Optimization Study of Military Material Based on Time U...

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2nd International Conference on Artificial Intelligence and automation control, AIAC 2024

作者： Gong, Hua Li, Shiqi Shi, Yiying School of Science Shenyang Ligong University Shenyang110159 China Liaoning Key Laboratory of Intelligent Optimization and Control for Ordnance Industry Shenyang110159 China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China

ISBN: (纸本)9798331529147

Aiming at the path optimization problem of military material based on time uncertainty, a multi-objective distribution model with a fuzzy time window was established with the shortest distribution path and the smallest time disturbance measure as the objective function. Combined weight method was used to assign weighted values to all kinds of military materials needed by combat points. The material urgency of the combat point is obtained, and then the time disturbance measurement is constructed. A genetic algorithm is used to solve the multiobjective optimization problem. © 2024 IEEE.

关键词： Genetic algorithms

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Potential Implications of Mixing Perturbations on Robust Stability for Linear Uncertain Systems 63

Potential Implications of Mixing Perturbations on Robust Sta...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Mao, Qi Chen, Jianqi Nanjing Normal University School of Electrical and Automation Engineering Nanjing China Jiangsu Key Laboratory of 3D Printing Equipment & Manufacturing Nanjing China Nanjing University Center for Advanced Control and Smart Operations Suzhou China

ISBN: (纸本)9798350316339

This paper is concerned with the stabilization problem of unstable systems with mixed gain and phase perturbations, thence elaborating on the exact computation of optimal robustness margins. We focus on non-minimum phase plants that are stabilized by proportional and proportional-integral (PI) controllers. Specifically, for such systems with mixed perturbations, we first show that the computation of optimal gain margin constitutes a constrained optimization problem. It is proved that the maximum gain margin is attained at zero integral gain, and the boundary value of proportional gain can be determined exactly. Via the Bilherz criterion, we next demonstrate that the maximal phase margin of non-minimum phase systems subject to mixed perturbations is also achieved at zero integral gain. It turns out that the calculation of optimal phase margin amounts to solving a concave optimization problem. Finally, we find that proportional-integral control and proportional control promise the same expressions of optimum robustness margins. Our explicit results clearly characterize the well-established dependence of the maximum robustness margins and/or the optimal controller coefficients on the system's unstable pole, nonminimum phase zero as well as uncertain perturbations. © 2024 IEEE.

关键词： Proportional control systems

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