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43rd Chinese control Conference, CCC 2024

作者： Li, Ao Chen, Xi Hunan University of Technology School of Rail Transit Zhuzhou412007 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9789887581581

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm, the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Lithology

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DMGA: A Directional-Mutation Genetic Algorithm for CDMS Problem of Kafka 21

DMGA: A Directional-Mutation Genetic Algorithm for CDMS Prob...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Ma, Hanbo Ma, Yaofei Yuan, Haitao Wang, Meijia Hu, Jingwei Wang, Yihuan Yang, Hanbo School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

ISBN: (纸本)9798350365221

With the increasing role of distributed message systems (DMS) represented by Kafka in handling large-scale data streams, it is critical to improve system performance by optimizing configuration parameters in different production environments. Due to the target system possessing numerous configuration parameters and the complex interactions between them, parameter optimization becomes a complex and time-consuming process that relies heavily on human effort and an iterative trial-and-error approach. At present, this type of configuration parameter problem has been classified as the Configuration of Distributed Message systems (CDMS) problem, for which the goal is to obtain the optimal set of parameters for achieving the best performance. In order to deal with this complex problem, an automatic optimization method is proposed in this paper, which combines an automatic script-based deployment and running framework with an improved Genetic Algorithm (GA) in cooperation with the Random Forest (RF) and statistical methods, named the Directional-Mutation Genetic Algorithm (DMGA). The framework and algorithm are designed to find the best configuration efficiently, obtaining optimal parameters accurately without human supervision. Actual results of comparison experiments based on the Kafka system show that the DMGA algorithm significantly improves the data throughput performance of Kafka, and its optimization speed is more efficient than the basic GA, highlighting its potential to quickly optimize Kafka's operational efficiency in different scenarios. © 2024 IEEE.

关键词： Genetic algorithms

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Exploring Image Generation for UAV Change Detection

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1061-1072页

作者： Xuan Li Haibin Duan Yonglin Tian Fei-Yue Wang Peng Cheng Laboratory Shenzhen 518000China IEEE State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Department of Automation University of Science and Technology of ChinaHefei 230027 State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense TechnologyChangsha 410073China

Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and ***,even the most advanced models require large amounts of data for model training and ***,sufficient labeled images with different imaging conditions are *** by computer graphics,we present a cloning method to simulate inland-water scene and collect an auto-labeled simulated *** simulated dataset consists of six challenges to test the effects of dynamic background,weather,and noise on change detection ***,we propose an image translation framework that translates simulated images to synthetic *** framework uses shared parameters(encoder and generator)and 22×22 receptive fields(discriminator)to generate realistic synthetic images as model training *** experimental results indicate that:1)different imaging challenges affect the performance of change detection models;2)compared with simulated images,synthetic images can effectively improve the accuracy of supervised models.

关键词： Change detection computer graphics image translation simulated images synthetic images unmanned aerial vehicles(UAVs)

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Terahertz Spectroscopic Characterization and Thickness Evaluation of Internal Delamination Defects in GFRP Composites

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Chinese Journal of Mechanical engineering 2023年第1期36卷 190-210页

作者： Walter Nsengiyumva Shuncong Zhong Manting Luo Bing Wang Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhou350108China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhou350108P.R.China School of Mechanical and Electrical Engineering Putian UniversityPutian351100China

The use of terahertz time-domain spectroscopy(THz-TDS)for the nondestructive testing and evaluation(NDT&E)of materials and structural systems has attracted significant attention over the past two decades due to its superior spatial resolution and capabilities of detecting and characterizing defects and structural damage in non-conducting *** this study,the THz-TDS system is used to detect,localize and evaluate hidden multi-delamination defects(i.e.,a three-level multi-delamination system)in multilayered GFRP composite *** obtain accurate results,a wavelet shrinkage de-noising algorithm is used to remove the noise from the measured time-of-flight(TOF)*** thickness and location of each delamination defect in the z-direction(i.e.,through-the-thickness direction)are calculated from the de-noised TOF signals considering the interaction between the pulsed THz waves and the different interfaces in the GFRP composite laminates.A comparison between the actual and the measured thickness values of the delamination defects before and after the wavelet shrinkage denoising process indicates that the latter provides better results with less than 3.712%relative error,while the relative error of the non-de-noised signals reaches 16.388%.Also,the power and absorbance levels of the THz waves at every interface with different refractive indices in the GFRP composite laminates are evaluated based on analytical and experimental *** present study provides an adequate theoretical analysis that could help NDT&E specialists to estimate the maximum thickness of GFRP composite materials and/or structures with different interfaces that can be evaluated by the ***,the accuracy of the obtained results highlights the capabilities of the THz-TDS for the NDT&E of multilayered GFRP composite laminates.

关键词： Glass-fiber-reinforced polymer-matrix(GFRP)composites Terahertz time-domain spectroscopy(THz-TDS) Nondestructive testing and evaluation(NDT&E) Stationary wavelet transform(SWT) Thickness evaluation Delamination defects

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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A Fully Distributed Hybrid control Framework For Non-Differentiable Multi-Agent Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1792-1800页

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Yue Wei the Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China IEEE the School of Electronic and Information Engineering Tongji UniversityShanghai 200082 the Peng Cheng Laboratory Shenzhen 518055China

This paper develops a fully distributed hybrid control framework for distributed constrained optimization *** individual cost functions are non-differentiable and *** on hybrid dynamical systems,we present a distributed state-dependent hybrid design to improve the transient performance of distributed primal-dual first-order optimization *** proposed framework consists of a distributed constrained continuous-time mapping in the form of a differential inclusion and a distributed discrete-time mapping triggered by the satisfaction of local jump *** the semistability theory of hybrid dynamical systems,the paper proves that the hybrid control algorithm converges to one optimal solution instead of oscillating among different *** simulations illustrate better transient performance of the proposed hybrid algorithm compared with the results of the existing continuous-time algorithms.

关键词： Distributed algorithm hybrid framework multiagent network non-differentiable optimization

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Adaptive Cooperative Estimation and Guidance Against Unknown Maneuvering Target

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Liu, Tianrun Chen, Yang-Yang Li, Shihua Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Advanced Ocean Institute of Southeast University Nantong226000 China

A critical challenge in missile guidance is the frequent inaccessibility of essential target information by on-board seekers. This paper studies the three-dimensional cooperative guidance issue of multiple missiles simultaneously attacking an unknown maneuvering target. Different from most existing research, the pitch and yaw lead angles of a maneuvering target are entirely unknown, while the position and velocity information is only accessible to neighboring missiles. An adaptive distributed estimator is designed to estimate the target information over a directed communication network, generating a transmitted target with similar maneuverability to the actual target for each missile. Boundedness of the estimation errors are guaranteed within a prescribed time. Subsequently, a modified guidance law that integrates proportional navigation (PN) and coordination components is developed for simultaneously tracking the trajectories of the transmitted targets. The superiority of the developed adaptive cooperative estimation and guidance approach is confirmed through simulations. © 1965-2011 IEEE.

关键词： adaptive estimate Cooperative guidance maneuvering target prescribed-time three-dimensional

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Hazard-Aware Weighted Advantage Combination for UAV Target Tracking and Obstacle Avoidance

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IEEE/CAA Journal of Automatica Sinica 2024年

作者： Xu, Lele Liu, Jian Chang, Xiaoguang Liu, Xuping Sun, Changyin The School of Artificial Intelligence Anhui University Hefei230601 China The School of Automation the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

In recent years, the rapid evolution of unmanned aerial vehicles (UAVs) has brought about transformative changes across various industries. However, addressing fundamental challenges in UAV technology, particularly target tracking and obstacle avoidance, remains crucial for wildlife protection, military industry security, etc. Many existing methods based on reinforcement learning to solve UAV multi-tasks need to be redesigned and retrained, and cannot be quickly and effectively extended to other scenarios. To this end, we propose a novel solution based on a hazard-aware weighted advantage combination for UAV target tracking and obstacle avoidance. First, we independently trained the UAV target tracking and obstacle avoidance using the Dueling Double Deep Q-Network reinforcement learning algorithm. Subsequently, in a multitasking scenario, we introduce the two pre-trained networks. Meanwhile, we design a weight determined by the present risk level encountered by the UAV. This weight is utilized to perform a weighted summation of the advantage values from both networks, eliminating the need for retraining to obtain the final action. We validate our approach through extensive simulation experiments in the robotics simulator known as CoppeliaSim. The results demonstrate that our method outperforms current state-of-the-art techniques, achieving superior performance in both tracking accuracy and avoidance of collisions. © 2013 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Single-ended protection method for hybrid HVDC transmission line based on transient voltage characteristic frequency band

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Protection and control of Modern Power systems 2023年第2期8卷 207-217页

作者： Hongchun Shu Shixin Wang Shunguang Lei Yunnan Key Laboratory of Green Energy Electric Power Measurement DigitalizationControl and ProtectionKunming University of Science and TechnologyKunming 650500Yunnan ProvinceChina School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001Heilongjiang ProvinceChina

Hybrid high-voltage direct current(HVDC)transmission has the characteristic of long transmission distance,complex corridor environment,and rapid fault evolution of direct current(DC)*** high fault current can easily cause irreversible damage to power devices,rapid and reliable line protection and isolation are necessary to improve the security and reliability of hybrid HVDC transmission *** address such requirement,this paper proposes a single-ended protection method based on transient voltage frequency band ***,the frequency characteristics of the smoothing reactor,DC filter,and DC line are analyzed,and the characteristic frequency band is defined.A fault criterion is then constructed based on the voltage characteristic frequency band energy,and faulty pole selection is performed according to the fault voltage characteristic frequency band energy *** proposed protection method is verified by simulation,and the results show that it can rapidly and reliably identify internal and external faults,accurately select faulty poles without data communication synchronization,and has good fault-resist-ance and anti-interference performance.

关键词： Boundary frequency characteristics Characteristic frequency band Hybrid HVDC Single-end protection Transient voltage

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Robust Speed Regulation of PMSM under Disturbances and Noises using Composite Model Predictive control

Robust Speed Regulation of PMSM under Disturbances and Noise...

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第42届中国控制会议

作者： Linxuan Mao Jinya Su Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

This paper presents a single-loop Model Predictive control strategy that incorporates a reduced-order Generalized Proportional Integral Observe and a Kalman filter to enhance the speed regulation of Permanent Magnet Synchronous Motor systems in the presence of complex disturbances and measurement noises. The proposed controller design seamlessly integrates the predictive control, disturbance observer, and state filter components, and it was evaluated through simulation comparisons. The performance of the proposed method is evaluated using various metrics, including maximum velocity drop, recovery time, and variance of steady-state error, which demonstrate its superior response performance and anti-disturbance ability when compared to other existing methods without state filtering.

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