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Improved Fixed-Time Stabilization of Fuzzy Neural Networks With Distributed Delay via Adaptive Sliding Mode control

IEEE TRANSACTIONS ON FUZZY SYSTEMS 2023年第6期31卷 2029-2043页

作者： Ren, Fangmin Wang, Xiaoping Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Educ Minist China Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan Peoples R China

This article investigates fixed-time stabilization of fuzzy neural networks with distributed delay by designing an adaptive sliding mode controller. First, according to stability theory and related inequalities, a new fixed-time stability theorem is put forward, and the settling time is given. In order to stabilize the system, a new integral sliding mode surface is designed, and the corresponding sliding mode control strategy and adaptive sliding mode control strategy are established. Some criteria that can be obtained, and it is shown that the neuronal states of neural networks will arrive at the sliding surface in a fixed time, and then approach zero along the sliding surface. Compared with existing sliding mode control techniques, this work extends the previous related results by choosing different parameters of the controller and the sliding mode manifold to gain various protocols. Finally, two examples are provided to verify the validity of the theorems in this work.

关键词： Stability criteria Sliding mode control Fuzzy neural networks Fuzzy control Asymptotic stability Convergence Neural networks Adaptive control fixed-time stable fuzzy neural network sliding mode control

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Dual-active Li‖Te-Bi liquid metal batteries with enhanced coulombic efficiency and cycling stability

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CHEMICAL COMMUNICATIONS 2025年第31期61卷 5750-5753页

作者： Guo, Yewei Li, Zehang Cu, Qiao Feng, Shaoming Zhang, Weixin Wang, Kangli Li, Haomiao Jiang, Kai Huazhong Univ Sci & Technol Sch Mat Sci & Engn Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn State Key Lab Adv Electromagnet Technol Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China

Tellurium (Te), a chalcogenide with higher electrical conductivity than sulfur (S) and selenium (Se), can be made into liquid metal batteries with high energy density. The Te-Bi alloy positive electrode inhibits Te dissolution and enhances lithium diffusion, which further improves the coulombic efficiency and cycling stability of lithium batteries. Due to the dual-activity mechanism, Li & Vert;Te5Bi5 achieves similar to 100% capacity utilization. Our results highlight a viable strategy for advancing high-voltage LMBs, providing an option for achieving long-life stationary energy storage solutions.

关键词： Bismuth alloys

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Source-Free Domain Adaptation (SFDA) for Privacy-Preserving Seizure Subtype Classification

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IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 2023年 31卷 2315-2325页

作者： Zhao, Changming Peng, Ruimin Wu, Dongrui Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Res Inst Shenzhen Shenzhen 518000 Peoples R China

Electroencephalogram (EEG) based seizure subtype classification is very important in clinical diagnostics. Source-free domain adaptation (SFDA) uses a pre-trained source model, instead of the source data, for privacy-preserving transfer learning. SFDA is useful in seizure subtype classification, which can protect the privacy of the source patients, while reducing the amount of labeled calibration data for a new patient. This paper introduces semi-supervised transfer boosting (SS-TrBoosting), a boosting-based SFDA approach for seizure subtype classification. We further extend it to unsupervised transfer boosting (U-TrBoosting) for unsupervised SFDA, i.e., the new patient does not need any labeled EEG data. Experiments on three public seizure datasets demonstrated that SS-TrBoosting and U-TrBoosting outperformed multiple classical and state-of-the-art machine learning approaches in cross-dataset/cross-patient seizure subtype classification.

关键词： Boosting ensemble learning EEG seizure subtype classification source-free domain adaptation transfer learning

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Unsupervised domain adaptation for cross-patient seizure classification

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JOURNAL OF NEURAL ENGINEERING 2023年第6期20卷 066002-066002页

作者： Wang, Ziwei Zhang, Wen Li, Siyang Chen, Xinru Wu, Dongrui Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Minist Educ Image Proc & Intelligent Contr Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Belt & Rd Joint Lab Measurement & Control Technol Wuhan 430074 Peoples R China

Objective. Epileptic seizure is a chronic neurological disease affecting millions of patients. Electroencephalogram (EEG) is the gold standard in epileptic seizure classification. However, its low signal-to-noise ratio, strong non-stationarity, and large individual difference nature make it difficult to directly extend the seizure classification model from one patient to another. This paper considers multi-source unsupervised domain adaptation for cross-patient EEG-based seizure classification, i.e. there are multiple source patients with labeled EEG data, which are used to label the EEG trials of a new patient. Approach. We propose an source domain selection (SDS)-global domain adaptation (GDA)-target agent subdomain adaptation (TASA) approach, which includes SDS to filter out dissimilar source domains, GDA to align the overall distributions of the selected source domains and the target domain, and TASA to identify the most similar source domain to the target domain so that its labels can be utilized. Main results. Experiments on two public seizure datasets demonstrated that SDS-GDA-TASA outperformed 13 existing approaches in unsupervised cross-patient seizure classification. Significance. Our approach could save clinicians plenty of time in labeling EEG data for epilepsy patients, greatly increasing the efficiency of seizure diagnostics.

关键词： EEG seizure classification transfer learning domain adaptation source domain selection

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Study of multilevel feature weighted fusion based image classification method for silicon single crystal growth process

Study of multilevel feature weighted fusion based image clas...

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2024 International Conference on image processing and Artificial Intelligence, ICIPAl 2024

作者： Xie, Ruidong Zhang, Zheqi Zhu, Pei Ma, Wenle Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510681514

A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification. © 2024 SPIE.

关键词： image classification

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Location and Capacity of Charging Station with Random Spatial-Temporal Distribution of Charging Demands 13

Location and Capacity of Charging Station with Random Spatia...

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

作者： Jiang, Man Cao, Zhong Niu, Yinsheng Zhang, Xueyu Liu, Xiao-Kang Yuan, Qi-Fan CentralChina Branch of State Grid Corporation of China Wuhan China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9798350315196

This paper studies the problem of location and capacity for direct charging (DC) fast charging stations (CS). A new model with the random spatial-temporal distribution of charging demands is proposed to plan both the location and capacity for CSs and is modeled as a nonlinear optimization problem with a comprehensive cost function and multi-variable that can be solved by an improved genetic algorithm. Further, the trip chain of EV users is considered to describe the traveling characteristics based on the origin-destination (OD) matrix, and then the Voronoi diagram is used to divide the service area of each CS. The effectiveness of both the model and the improved genetic algorithm is demonstrated through the final simulation results and comparative analyses. © 2023 IEEE.

关键词： Location

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Path planning for a tracked robot traversing uneven terrains based on tip-over stability

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ASIAN JOURNAL OF control 2023年第5期25卷 3569-3583页

作者： Zhao, Jiangbo Zhang, Jiaquan Liu, Hanze Wang, Junzheng Chen, Zhihua Beijing Inst Technol Key Lab Intelligent Control & Decis Complex Syst Beijing Peoples R China Nanchang Hangkong Univ Key Lab Jiangxi Prov Image Proc & Pattern Recognit MOE Key Lab Nondestruct Testing Technol Nanchang Peoples R China Nanchang Hang kong Univ Beijing Inst Technol Sch Automation Sch Informat Engn Nanchang Peoples R China

In the real-world environment, the path planning method of tracked robot is widely studied when driving on uneven terrain. How to solve the problem that the traditional path planning algorithm cannot adapt to uneven terrain because of the constraints of obstacle avoidance and path length is a challenge for tracked robots. In this paper, a stability-based path planning framework for tracked robot is proposed to reduce the risk of rollover when the tracked robot passes through uneven terrain. First, a virtual plane method is proposed to estimate the attitude of tracked robot. Second, on this basis, a dynamic high-stability path evaluation algorithm for tracked robot based on force angle stability margin (FASM) is proposed, which transforms the stability-based path planning problem into a hypergraph problem. Moreover, considering that the optimization problem is strongly nonlinear and nonconvex, a hybrid algorithm of covariance matrix adaptive evolution strategy (CMAES) and Levenberg-Marquardt (LM) is designed under the framework of generalized graph optimization (G2O) to improve the solution efficiency. Finally, simulation and experiments show that the stability-based path planning framework can effectively plan the high-quality path, and the maximum stability of the tracked robot is 0.9156 when the robot crosses uneven terrain using optimal path 2.

关键词： CMAES estimate attitude FASM path planning stability

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Statistical Feasibility Robust Optimization With Polyhedron Uncertainty Set for Hydrogen-Data Center Microgrid Operations

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 9884-9902页

作者： Duan, Juntao Li, Yuanzheng Li, Yang Yang, Pu Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Northeast Elect Power Univ Sch Elect Engn Jilin 132000 Peoples R China Tencent Technol Shenzhen Co Ltd Shenzhen 518057 Guangdong Peoples R China

Robust optimization (RO) has been widely used in the hydrogen-data-center microgrid (H-2- DCMG) optimal operations. However, the operation results based on RO are too conservative. Statistical feasibility can be introduced into RO to reduce conservatism. Therefore, statistical feasibility-based RO is adopted in the H-2- DCMG operations optimization. In this study, a data-driven statistical-feasibility-based robust rolling optimization framework is constructed for the optimal operations of the c-DCMG. In this framework, DC temperature is influenced by the uncertain outside temperature, and an uncertainty set is needed to express the uncertain outside temperature. Unfortunately, the existing studies that construct the uncertainty set satisfying statistical feasibility only constructs the ellipsoid uncertainty sets. The ellipsoid uncertainty sets will be converted into the second-order cone constraints, which will increase the complexity when solving. In this study, the Statistical-Guarantee-based Vertex Link (SGVL) algorithm is proposed to construct the polyhedron uncertainty sets, which are used to describe the uncertainty of the outside temperature. Moreover, statistical feasibility-based DC temperature bound is guaranteed by the optimal operations obtained based on these uncertainty sets. Compared with the traditional ellipsoid uncertainty set, the polyhedron uncertainty set can reduce the complexity of the optimization problem and improve the efficiency of the solution process. Case studies based on the real-world temperature dataset are processed. The results show that the introduction of statistical feasibility can reduce the total operation cost by 0.29%similar to 0.64%. The average solving time of the optimization problems based on the polyhedron uncertainty sets constructed using the SGVL algorithm also reduces by 7%similar to 13%. The cases also verify that other uncertainty parameters and different kinds of forecasters do not influence the performance and e

关键词： Uncertainty Optimization Temperature distribution Upper bound Servers Microgrids Heating systems Data centers Hydrogen Greenhouse gases Hydrogen energy storage system data center microgrid statistical feasibility robust optimization

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A large-scale group SLIM considering expert credibility under social network to estimate human error probabilities in the railway driving process

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 255卷

作者： Zhou, Jian-Lan Zhou, Ya-Lun Xiao, Ren-Bin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci Technol Res Inst Shenzhen 518057 Peoples R China

The Large-scale Group Success Likelihood Index Method (LG-SLIM) can eliminate bias caused by a single expert in human error assessment. The traditional LG-SLIM uses trust degrees to cluster and reach a consensus. However, the existing clustering algorithms do not consider the trust degrees between a given pair of experts to be multiple and vary according to different evaluated tasks. Besides, the existing consensus models do not consider various combinations of the evaluated tasks and trusted experts' professions when managing trust degrees and self-confidence. Therefore, the similarity-trust-based clustering algorithm is improved using the comprehensive trust degree integrated from diverse trust degrees concerning all evaluated tasks. Moreover, expert credibility is proposed to reflect the quality of the expert's evaluation results, determined by self-confidence and trust degree simultaneously according to various combinations of the expert profession and target task. Accordingly, under the social network derived from expert credibility, the incompatible outliers change their opinions by referring to the views of those with the highest expert credibility. Finally, the sensitivity experiment and comparative analysis verify the effectiveness of the proposed model. The proposed LG-SLIM model is useful for human error assessment when critical operations need many experts to obtain reliable and accurate results.

关键词： Railway operation Success likelihood index method Human error analysis Expert credibility Social network Large-scale group decision-making

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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