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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Zhu, Xiaohan Bu, Ran Li, Zhen Xu, Fan Wang, Hesheng School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Automation China Artificial Intelligence Research Institute School of Information and Control Engineering China University of Mining and Technology China

ISBN: (纸本)9781665481090

Soft manipulators are known for their superiority in coping with high-safety-demanding interaction tasks, e.g., robot-assisted surgeries, elderly caring, etc. Yet the challenges residing in real-time contact feedback have hindered further applications in precise manipulation. This paper proposes an end-to-end network to estimate the 3D contact force of the soft robot, with the aim of enhancing its capabilities in interactive tasks. The presented method features directly utilizing monocular images fused with multidimensional actuation information as the network inputs. This approach simplifies the preprocessing of raw data compared to related studies that utilize 3D shape information for network inputs, consequently reducing configuration reconstruction errors. The unified feature representation module is devised to elevate low-dimensional features from the system's actuation signals to the same level as image features, facilitating smoother integration of multimodal information. The proposed method has been experimentally validated in the soft robot testbed, achieving satisfying accuracy in 3D force estimation (with a mean relative error of 0.84% compared to the best-reported result of 2.2% in the related works). © 2024 IEEE.

关键词： Robotic surgery

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Adaptive Prescribed Finite-Time Bipartite Consensus control for Nonaffine Nonlinear MASs Under Structurally Unbalanced Topology

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3532-3541页

作者： Wang, Xiaomei Song, Yongduan Zhao, Xudong Wang, Huanqing Wang, Ding Niu, Ben Chongqing University School of Automation Chongqing400044 China Shandong Normal University School of Information Science and Engineering Shandong Jinan250014 China Dalian University of Technology School of Control Science and Engineering Liaoning Dalian116023 China Bohai University College of Mathematical Sciences Liaoning Jinzhou121013 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Sichuan University School of Electrical Engineering Chengdu610065 China

This article investigates an adaptive bipartite consensus tracking control algorithm for a class of heterogeneous nonaffine nonlinear multiagent systems (MASs) with prescribed finite-time tracking performance under an unbalanced communication topology. In the case of an unbalanced digraph, a novel locally optimal bipartition strategy is proposed to transform the unbalanced communication topology into a structurally balanced one, thereby enabling the implementation of bipartite consensus tracking control. To achieve the expected tracking performance, the design philosophy focuses on developing a prescribed finite-time performance function (PFTPF), capable of preassigning the convergence time and accuracy precisely beforehand. The explored adaptive control algorithm can ensure that the whole signals concerning the closed-loop MASs remain bounded while the bipartite consensus errors converge to a predetermined range around zero within the prescribed finite time. Ultimately, the simulation results on robotic systems prove the availability of the developed design solution. © 2013 IEEE.

关键词： Topology

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Dispatch of a Coal Mine-Integrated Energy System:Optimization Model with Interval Variables and Lower Carbon Emission

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Tsinghua Science and technology 2024年第5期29卷 1441-1462页

作者： Hejuan Hu Xiaoyan Sun Bo Zeng Dunwei Gong Yong Zhang Patrick Nyonganyi Henerica Tazvinga School of Information and Control Engineering ChinaUniversity of Mining and TechnologyXuzhou 221116China Laboratory of Alternate Electrical PowerSystem with Renewable Energy Sources North ChinaElectric Power UniversityBeijing 102206China School of Information Science andTechnology Qingdao University of Science and TechnologyQingdao 266061China Department of Automation Tsinghua UniversityBeijing 100084China South Africa WeatherService Pertoria 0001South Africa

In the coal mining process,a large amount of Coal Mine-Associated energy(CMAE),such as coal mine methane and underground wastewater,is *** on the modeling and optimization dispatching of a Coal Mine-Integrated Energy System(CMIES)with CMAE effectively saves energy and reduces carbon *** has great uncertainties owing to the affections of the hydrogeology conditions and mining *** addition,thermal loads have high comfort requirements in mines,which brings great challenges to the optimization dispatching of ***,this paper studies the architecture and solution of CMIESs with a flexible thermal load and source-load ***,to effectively improve the electric and thermal conversion efficiency,the architecture of CMIES,including a concentrating solar power station,is ***,for the scheduling model with bilateral uncertainty,the interval representation method with interval variables is proposed,and a multi-objective scheduling model based on the interval variables and flexible thermal load is ***,we propose a solution method for the model with interval variables.A case study is conducted to demonstrate the performance of our model and method for lowering carbon emissions and cost.

关键词： Integrated Energy Systems(IESs) Coal Mine-Integrated Energy Systems(CMIES) bilateral uncertainties concentrating solar power station interval optimization

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USDE-Based Task-Space Bilateral Teleoperator control Design with Time Delay 16th

USDE-Based Task-Space Bilateral Teleoperator Control Design ...

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16th International Conference on Modelling, Identification and control, ICMIC 2024

作者： Luo, Xin Ma, Jun Wang, Xian Na, Jing Xing, Yashan Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9789819617760

In this paper, we present a control strategy for bilateral teleoperators operated in the task space, which is designed to estimate the uncertain dynamics. To implement this proposed strategy, we develop a straightforward yet robust unknown system dynamics estimator (USDE) by incorporating a low-pass filtering operation. By using the USDE, we can eliminate the impact of unmodeled system dynamics without the need to measure the acceleration signal. Furthermore, the proposed USDE offers the advantages of requiring only one tuning parameter and being easily adjustable compared to conventional estimators. The convergence of the estimation error associated with the unmodeled system dynamics and the stability of the closed-loop control system are both rigorously demonstrated through Lyapunov’s theorem. Ultimately, the superior performance of our method, as evidenced by enhancing motion synchronization and stability, is confirmed through simulation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Time delay

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Robust Consensus Tracking control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 427-438页

作者： Pan Yu Kang-Zhi Liu Xudong Liu Xiaoli Li Min Wu Jinhua She the Faculty of Information Technology and the Beijing Institute of Artificial Intelligence Beijing University of TechnologyBeijing 100124China IEEE the Department of Electrical and Electronic Engineering Chiba UniversityChiba 263-8522Japan the Beijing Aerospace Automatic Control Institute Beijing 100854China the School of Automation China University of GeosciencesWuhan 430074China the School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan

In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed *** is of two-degree-of-freedom ***,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of *** condition for asymptotic disturbance rejection is ***,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection ***,a robust stabilization condition with less conservativeness is derived for the whole multi-agent ***,a design algorithm is ***,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.

关键词： Directed graph distributed control disturbance rejection dynamic uncertainties multi-agent systems robust control

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Dynamic Quantized control of Fuzzy Semi-Markov Jump Systems With Fading Channels: An Improved Event-Triggered Mechanism

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3519-3531页

作者： Hu, Meng-Jie Park, Ju H. Cheng, Jun Wang, Yan-Wu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of Guangxi Normal University School of Mathematics and Statistics Guilin541006 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China

This article focuses on the dynamic quantized control for Takagi-Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under fading channels and deception attacks, employing an improved event-triggered mechanism (ETM) strategy. Specifically, a more generalized semi-Markov process (SMP) that is governed by a higher-level deterministic switching signal (HLDSS) is addressed. A novel dynamic ETM is skillfully developed based on the information of quantization and two internal dynamic adjusting variables to further enhance the network bandwidth utilization. The dual asynchronous phenomenon between the plant and controller (asynchronous modes and mismatched premise variables) is addressed. This implies that the designed controller is not required to share the same membership functions and modes as the plant, establishing a more rational structure. The hidden semi-Markov model (HSMM) is attained to characterize the stochastic varying channel fading amplitudes. The Lyapunov function incorporating mode and fuzzy information is constructed to establish sufficient criteria ensuring the strictly dissipative performance and mean-square exponential stability (MSES) of the resulting closed-loop systems, and a new security fuzzy dual asynchronous controller is then developed. Finally, the efficacy and applicability of the results are demonstrated through numerical and practical examples. © 2025 IEEE.

关键词： Membership functions

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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

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Computer Modeling in engineering & Sciences 2023年第12期137卷 2163-2192页

作者： Ali S.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： Stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

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Self-adaptive Bat Algorithm With Genetic Operations

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1284-1294页

作者： Jing Bi Haitao Yuan Jiahui Zhai MengChu Zhou H.Vincent Poor School of Software Engineering Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Department of Electrical Engineering Princeton UniversityPrinceton NJ 08544 USA IEEE

Swarm intelligence in a bat algorithm(BA)provides social *** operations for reproducing individuals in a genetic algorithm(GA)offer global search ability in solving complex optimization *** integration provides an opportunity for improved search ***,existing studies adopt only one genetic operation of GA,or design hybrid algorithms that divide the overall population into multiple subpopulations that evolve in parallel with limited interactions *** from them,this work proposes an improved self-adaptive bat algorithm with genetic operations(SBAGO)where GA and BA are combined in a highly integrated ***,SBAGO performs their genetic operations of GA on previous search information of BA solutions to produce new exemplars that are of high-diversity and *** by these exemplars,SBAGO improves both BA’s efficiency and global search *** evaluate this approach by using 29 widely-adopted problems from four test *** is also evaluated by a real-life optimization problem in mobile edge computing *** results show that SBAGO outperforms its widely-used and recently proposed peers in terms of effectiveness,search accuracy,local optima avoidance,and robustness.

关键词： Bat algorithm(BA) genetic algorithm(GA) hybrid algorithm learning mechanism meta-heuristic optimization algorithms

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Informer-LSTM-EWMA for Panax Notoginseng with Prediction of Early Intervention Time 13

Informer-LSTM-EWMA for Panax Notoginseng with Prediction of ...

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

作者： Ye, Jiahui Yang, Chunxi Zhang, Xiufeng Zhang, Jin Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650504 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650504 China

ISBN: (纸本)9798350361674

Panax notoginseng is one of economic crop with significant medicinal value in southwest China. However, traditional extensive fertilization and irrigation method usually damages the soil, making it difficult to achieve sustainable cultivation of Panax notoginseng. In order to assess the growth status of Panax notoginseng and take timely action, this paper proposed an Informer-LSTM-EWMA model to predict the growth trend of Panax notoginseng in cultivation fields. In the experimental greenhouse, we set up two experimental fields A and B to verify the feasibility of the proposed method. Firstly, wavelet denoising is utilized on the date collected by the sensor. Then, Informer and Long short-term Memory (LSTM) are used to train the denoised data to obtain data prediction. Further process the predicted data through Exponential Weighted Moving Average (EWMA) for trend prediction. Finally, the early intervention time is obtained by searching for the maximum value. The results indicate that the model can predict early intervention time and its predictive performance is far better than that of a single model. © 2024 IEEE.

关键词： Prediction models

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