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3rd International Conference on Electronic Information engineering and Computer Communication, EIECC 2023

作者： Li, Xiunan Chen, Yunjun School of Control Science and Engineering Tiangong University Tianjin China

ISBN: (纸本)9798350359961

This paper focuses on the dynamic event-Triggered (DET) integral sliding mode control (SMC) problem in linear systems with disturbances via state observers. Unlike the state event-Triggered strategy, a dynamic event-Triggered mechanism has been added to reduce communication transmission effectively under the sensor-To-controller channel. To reduce chattering while preserving the rapidly changing sliding variable, an improve DET integral sliding mode controller with a power-reaching law is developed. Both the linear matrix inequalities (LMls) and the Lyapunov stability theory provide sufficient conditions for the dynamic sliding mode. Subsequently, a positive lower bound was determined to avoid the Zeno phenomenon. Finally, the validity of the scheme was verified through simulations. © 2023 IEEE.

关键词： dynamic event-Triggered (DET) integral sliding mode control (SMC) linear matrix inequalities (LMls) state observer

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Dynamic Capacitated Vehicle Routing Problem with Stochastic Requests Using Deep Reinforcement Learning

Dynamic Capacitated Vehicle Routing Problem with Stochastic ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Tang, Kaiqiang Fu, Huiqiao Liu, Jiasheng Deng, Guizhou Lu, Yuanyang Chen, Chunlin School of Management and Engineering Nanjing University Department of Control Science and Intelligent Engineering Nanjing210093 China

ISBN: (纸本)9781665410205

With the rapid growth of industries like e-commerce, food delivery, and ride-hailing, research on the Vehicle Routing Problem (VRP) is becoming increasingly relevant. However, most of the research in the field of VRP is based on static delivery tasks. In such tasks, the information about customer and order requests is provided before the delivery vehicle departs from the depot, and it remains constant during delivery. However, in the real world, the delivery tasks are often dynamic, where only some orders are known before the vehicle departs from the depot, and the rest of the orders are disclosed over time [1]. © 2024 IEEE.

关键词： Stochastic systems

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Transient Stability Improvement of Grid-Forming Converters Through Voltage Amplitude Regulation 49

Transient Stability Improvement of Grid-Forming Converters T...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Si, Wenjia Fang, Jingyang The School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350331820

Grid-forming converters have been identified as an enabling technology in modern power systems. However, the unstable operation of grid-forming converters under large disturbances poses a significant challenge. To address the challenge, this article delves into the transient stability of grid-forming converters and proposes a method to enhance it. First, this article reveal that the active power injection and absorption of grid-forming converters are asymmetrical. Subsequently, the method of voltage amplitude regulation is proposed to improve the transient stability. In addition, this article derives the critical values of voltage amplitude in transient periods to guide controller design. Finally, simulation and experimental results are provided to validate the effectiveness of the proposed methods. © 2023 IEEE.

关键词： Stability

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Time-frequency Feature-based Detection of Small Target on Sea-Surface 5

Time-frequency Feature-based Detection of Small Target on Se...

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5th International Academic Exchange Conference on science and Technology Innovation, IAECST 2023

作者： Cheng, Yi Wang, Yang Tiangong University School of Control Science and Engineering Tianjin China

ISBN: (纸本)9798350357738

This paper proposes a small target detection algorithm for sea-surface based on time-frequency analysis. Firstly, the echo signal is transformed by short-time Fourier transform (STFT) and smooth pseudo-Wigner-Ville distribution (SPWVD) simultaneously, and then the time-frequency matrices are processed for denoising by using K-medoids clustering algorithm. The time-frequency feature Doppler frequency stability (DFS) is extracted from the optimized time-frequency matrix, and the sea clutter is discriminated from the target according to the difference of the DFS. Finally, the experimental results based on the IPIX radar measured data show that the proposed detector improves the probability of detection by 6.2% and 7.1% over the time-frequency tri-feature detector when the observation time is 0.512s and 1.024s, respectively. © 2023 IEEE.

关键词： Wigner-Ville distribution

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Q-Learning Design for Discrete-Time Stochastic Zero-Sum Games

Q-Learning Design for Discrete-Time Stochastic Zero-Sum Game...

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2023 China Automation Congress, CAC 2023

作者： Guo, Liangyuan Wang, Bingchang Dong, Hailing School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350303759

This study explores the application of the model-free Q-Learning algorithm in discrete-time linear quadratic stochastic zero-sum games. The main contribution is two-fold: firstly, extending the zero-sum game concept to stochastic situation and resolving it through a model-based approach;secondly, introducing a model-free Q-Learning algorithm as an innovative method, differing from conventional policy iteration and value iteration. Detailed mathematical demonstrations are included, validating the model-free Q-Learning algorithm's convergence within this research. A numerical example is provided to demonstrate the algorithm's effectiveness. © 2023 IEEE.

关键词： Iterative methods

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Cross-modal Speech Separation Without Visual Information During Testing

Cross-modal Speech Separation Without Visual Information Dur...

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Liu, Yinggang Deng, Yuanjie Wei, Ying Shandong University School of Control Science and Engineering Jinan China

ISBN: (纸本)9798350300260

Visual information plays an important role in speech separation. It has been illustrated by many studies that audio-visual speech separation has better performance than audio-only speech separation. However, it is not always possible to capture high-quality visual information due to various factors. In this paper, we propose a novel audio-visual matching-based speech separation method. The network exploits audiovisual correlations in the training process, but does not require visual information during testing. The proposed cross-modal speech separation method is evaluated on GRID dataset. Experimental results show that the proposed method has a significant improvement in multiple evaluation metrics for different types of mixtures compared with other advanced speech separation methods. © 2023 IEEE.

关键词： audio-visual matching speech separation time domain

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RHC-Based Consensus of Multi-Agent Systems with Simultaneous Packet Dropout and Input Delay

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Journal of Systems science & Complexity 2022年第4期35卷 1262-1277页

作者： XU Juanjuan ZHANG Zhaorong School of Control Science and Engineering Shandong UniversityJinan250061China School of Electrical Engineering and Computer Science University of NewcastleNewcastleCallaghanNSW2308Australia

This paper is concerned with the multi-agent systems with both packet dropout and input delay.A novel receding horizon control(RHC)based consensus protocol is proposed by solving a distributed RHC based optimization *** novelty of the optimization problem lines in the involvement of the neighbours’predictor information in the cost *** on the derived RHC based consensus protocol,the necessary and sufficient condition for the mean-square consensus is *** addition,the authors give a specific sufficient condition to guarantee the mean-square consensus.

关键词： Consensus delay packet dropout predictor-like protocol receding horizon control

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A Deep Transfer Learning Framework for Li-ion Battery Temperature Prediction Based on LSTM Pretraining Model 2

A Deep Transfer Learning Framework for Li-ion Battery Temper...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Ren, Fei Lu, Dong Cui, Naxin School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350313765

Due to the promotion of electric vehicles and new energy, lithium-ion batteries (LIBs) have been widely used. However, temperature exerts a significant impact on the performance and safety of LIBs during operation. Therefore, it is very important to predict the temperature of LIBs and implement thermal warning. To address this issue, this paper designs a deep transfer learning method based on Long Short Term Memory (LSTM) pretraining fine-tuning model to predict the temperature of LIBs. First, select the input parameters according to the law of thermodynamics and pearson correlation coefficient. Secondly, use autocorrelation coefficient to analyze the data state correlation, and select the step size of the input parameters. Then, use LSTM to pretrain the model and freeze the relevant parameters. Finally, migrate the frozen model to the target domain and add a fully connected layer for fine-tuning training to predict battery temperature. To confirm the efficiency of the method, several complete experimental verifications were carried out on the data set of UDDS dynamic working conditions and temperatures from 0°C to 40°C. Experimental results demonstrate that the proposed method significantly improves the accuracy of LIBs temperature prediction compared to other popular data-driven models. © 2023 IEEE.

关键词： LIBs long short term memory pretraining fine-tuning model temperature transfer learning

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Adjustable patch and feature prior token-based transformer for weakly supervised semantic segmentation

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International Journal of Computers and Applications 2024年第7期46卷 445-454页

作者： Li, Linjuan Zhang, Haoxue Xie, Gang Bai, Yanhong School of Electronic and Information Engineering Taiyuan University of Science and Technology Taiyuan China Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China

Weakly supervised semantic segmentation is a challenging task, utilizing only low-cost weak supervision to produce pixel-level predictions. Existing transformer-based methods for weakly supervised semantic segmentation have some limitations: (1) Fixing patch size might destroy the structured semantics, which is unfriendly to objects of different scales, and (2) Ignoring the prior features when using multi-head attention mechanisms might lead to inaccurate segmentation localization. To tackle these issues, we proposed an effective transformer framework coupled with the adjustable patch and prior feature tokens, termed as APFPformer, in which an adjustable patch module is developed to split the image according to the area of the salient object for preserving the structured semantics in patches. A prior feature token module is devised to exploit the edge and texture information as prior tokens, ensuring the gain of discriminative representation. Additionally, a single-stage scheme is applied to reduce the computation and rapid segmentation process. Our experiments demonstrate the superiority of our approach over early methods, gaining competitive mean Intersection-over-Union scores of 67.9% on the PASCAL VOC2012 dataset and 40.2% on the MS COCO dataset. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Semantic Segmentation

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Adaptive IMM Algorithm for Highly Maneuverable Targets based on Cubature Kalman Filter 5

Adaptive IMM Algorithm for Highly Maneuverable Targets based...

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5th International Academic Exchange Conference on science and Technology Innovation, IAECST 2023

作者： Liu, Mingyang Xu, Guowei Cheng, Yi Guo, Yuanyuan Tiangong University School of Control Science and Engineering Tianjin China

ISBN: (纸本)9798350357738

Highly maneuverable targets have the characteristics of high speed and variable motion trajectories. The traditional Interacting Multiple Model (IMM) algorithm has low tracking accuracy. An improved strong tracking CKF adaptive interacting multiple model algorithm is proposed. Based on IMM-CKF, the CS-Jerk model is used in the sub-model of the IMM algorithm to enhance its adaptability to high maneuvering targets, which introduced SVD algorithm to solve the problem of Cholesky decomposition failure in CKF due to model dimension expansion;Aiming at the problem of high computational complexity in existing strong tracking CKF algorithms, an improved strong tracking filtering CKF algorithm is proposed to reduce computational complexity;An adaptive Markov transition probability algorithm is proposed, which makes the model probabilities changing more real and enhance the proportion of matching model, improves the filtering accuracy. Simulation results indicate that, compared with IMM algorithm, the proposed algorithm improves tracking accuracy by 10.02%, compared with strong tracking IMM-CKF algorithm, the proposed algorithm reduces filtering time by 45.84%. © 2023 IEEE.

关键词： Target tracking

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