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A Real-Time Semantic Segmentation Method Based on Transformer for Autonomous Driving

Computers, Materials & Continua 2024年第12期81卷 4419-4433页

作者： Weiyu Hao Jingyi Wang Huimin Lu Donald Bren School of Information and Computer Sciences University of CaliforniaIrvineCA 92612USA Department of Control Engineering Kyushu Institute of TechnologyKitakyushu804-8550Japan School of Automation Southeast UniversityNanjing210096China

While traditional Convolutional Neural Network(CNN)-based semantic segmentation methods have proven effective,they often encounter significant computational challenges due to the requirement for dense pixel-level predictions,which complicates real-time *** address this,we introduce an advanced real-time semantic segmentation strategy specifically designed for autonomous driving,utilizing the capabilities of Visual *** leveraging the self-attention mechanism inherent in Visual Transformers,our method enhances global contextual awareness,refining the representation of each pixel in relation to the overall *** enhancement is critical for quickly and accurately interpreting the complex elements within driving sce-narios—a fundamental need for autonomous *** experiments conducted on the DriveSeg autonomous driving dataset indicate that our model surpasses traditional segmentation methods,achieving a significant 4.5%improvement in Mean Intersection over Union(mIoU)while maintaining real-time *** paper not only underscores the potential for optimized semantic segmentation but also establishes a promising direction for real-time processing in autonomous navigation *** work will focus on integrating this technique with other perception modules in autonomous driving to further improve the robustness and efficiency of self-driving perception frameworks,thereby opening new pathways for research and practical applications in scenarios requiring rapid and precise decision-making *** experimentation and adaptation of this model could lead to broader implications for the fields of machine learning and computer vision,particularly in enhancing the interaction between automated systems and their dynamic environments.

关键词： Visual transformer semantic segmentation autonomous driving

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Multi-objective Optimization of the Interior Permanent Magnet Synchronous Motor for Electric Vehicles 6

Multi-objective Optimization of the Interior Permanent Magne...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Huang, Changchuang Kou, Baoqaun Zhao, Xiaokun Harbin Institute of Technology Electrical Engineering and Automation Heilongjiang China Northeast Forestry University Computer and Control Engineering Heilongjiang China

ISBN: (纸本)9798350346671

Permanent magnet synchronous motors (PMSMs) are widely used in various fields due to their high efficiency, high power factor and small volume. In this paper, a segmented permanent magnet interior permanent magnet synchronous motor (IPMSM) is proposed and optimized. First, the topology of the IPMSM is introduced. Second, multi-objective optimization is performed by non-dominated sorting genetic algorithm-II (NSGA-II) using rotor structure parameters as optimization variables, saliency ratio as constraint, electromagnetic torque and constant-power speed range as objective functions. Then, the electromagnetic characteristics of the initial IPMSM and the optimized IPMSM are analyzed and compared. The results show that the torque and constant-power speed range of the optimized motor are improved, which verifies the validity of the optimization method. The proposed motor is suitable for electric vehicles, which require large torque at low speeds and wide constant-power speed range at high speeds. © 2023 IEEE.

关键词： Multiobjective optimization

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Development of Artificial Intelligence Supported Tool for Anomaly Detection in Cloud Computing Systems 4

Development of Artificial Intelligence Supported Tool for An...

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4th International Conference on Electrical, Communication and Computer engineering, ICECCE 2023

作者： Aktas, Gorkem Ipek, Batuhan Konukoglu, Emin Ali Aydin, Yucel Control and Automation Engineering Istanbul Technical University Istanbul Turkey Electronics and Communication Engineering Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9798350369694

In the rapidly evolving landscape of Internet of Things (IoT) and Cloud systems, the complexity and scale of these technologies demand innovative solutions for efficient error detection and management. This paper proposes a robust framework for anomaly detection in cloud computing systems, emphasizing the critical role of automation and artificial intelligence (AI). The approach integrates Continuous Integration, Continuous Deployment (CICD) principles with AI-driven anomaly detection techniques to enhance system reliability and minimize risks. The study introduces a novel method employing one-dimensional convolutional layers and Autoencoder architecture to preprocess and analyze system metrics, enabling the development of an adaptive and customized anomaly detection system. The proposed framework is implemented through a Python-based agent, utilizing specific libraries and Continuous Integration/Continuous Deployment (CI/CD) processes executed via Jenkins. The agent is tested and deployed on Kubernetes, demonstrating its effectiveness in dynamic and complex environments. The results highlight the significance of iterative optimization, emphasizing continuous monitoring and adaptation for ensuring the robustness and reliability of cloud computing systems. This research contributes valuable insights into enhancing the efficiency of anomaly detection in large-scale cloud systems, paving the way for further advancements in the field of IoT and cloud technologies. © 2023 IEEE.

关键词： Anomaly detection

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Deep reinforcement learning guidance with impact time control

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Journal of Systems engineering and Electronics 2024年第6期35卷 1594-1603页

作者： LI Guofei LI Shituo LI Bohao WU Yunjie School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China Beijing Institute of Control and Electronic Technology Beijing 100038China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

In consideration of the field-of-view(FOV)angle con-straint,this study focuses on the guidance problem with impact time control.A deep reinforcement learning guidance method is given for the missile to obtain the desired impact time and meet the demand of FOV angle *** basis of the framework of the proportional navigation guidance,an auxiliary control term is supplemented by the distributed deep deterministic policy gradient algorithm,in which the reward functions are developed to decrease the time-to-go error and improve the terminal guid-ance *** numerical simulation demonstrates that the missile governed by the presented deep reinforcement learning guidance law can hit the target successfully at appointed arrival time.

关键词： impact time deep reinforcement learning guidance law field-of-view(FOV)angle deep deterministic policy gradient

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Dynamic load altering attack detection based on adaptive fading Kalman filter in smart grid

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IET Generation, Transmission and Distribution 2024年第2期18卷 303-313页

作者： Li, Jian Sun, Chaowei Yang, Shuxian Su, Qingyu School of Automation Engineering Northeast Electric Power University Jilin Jilin China Jilin Provincial Key Laboratory of Advanced Control Technology of Smart Energy Northeast Electric Power University Jilin Jilin China

This paper mainly studies a detection method of dynamic load altering attacks (D-LAAs) in smart grids. First, communication factors are considered, and a smart grid discrete system model under D-LAA attack is established. Second, for closed-loop D-LAAs, an adaptive fading Kalman filter (AFKF) is designed to estimate the states of smart grids with Gaussian noise in real time, and a Euclidean distance ratio detection algorithm based on AFKF is proposed to detect D-LAAs. Moreover, the proposed detection algorithm can identify D-LAAs even in the presence of noise in the measurement data, significantly enhancing the speed of attack detection. Finally, take a smart grid with three generators and six buses as an example. Its feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified by simulations. The simulations are carried out through the real-time hardware-in-the-loop simulation platform, which is mainly composed of StarSim and multi-tasking devices. © 2024 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Cyber Physical System

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Higher-order properties and extensions for indirect MRAC and APPC of linear systems

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Science China(Information Sciences) 2024年第4期67卷 218-238页

作者： Yanjun ZHANG Zhipeng ZHANG Jian SUN Lei WANG Kangkang ZHANG National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center College of Control Science and Engineering Zhejiang University Department of Electrical and Electronic Engineering Imperial College London KIOS Research and Innovation Center of Excellence University of Cyprus

Recently, a reference derived some new higher-order output tracking properties for direct model reference adaptive control（MRAC） of linear time-invariant（LTI） systems: limt→∞ e（i）（t） = 0, i = 1,..., n*-1, where n*and e（i）（t） denote the relative degree of the system and the i-th derivative of the output tracking error, respectively. However, a naturally arising question involves whether indirect adaptive control（including indirect MRAC and indirect adaptive pole placement control） of LTI systems still has higher-order tracking properties. Such properties have not been reported in the literature. Therefore, this paper provides an affirmative answer to this question. Such higher-order tracking properties are new discoveries since they hold without any additional design conditions and, in particular, without the persistent excitation condition. Given the higher-order properties, a new adaptive control system is developed with stronger tracking features.（1） It can track a reference signal with any order derivatives being unknown.（2） It has higher-order exponential or practical output tracking properties.（3） Finally, it is different from the usual MRAC system, whose reference signal's derivatives up to the n*order are assumed to be known. Finally, two simulation examples are provided to verify the theoretical results obtained in this paper.

关键词： higher-order tracking indirect adaptive control model reference adaptive control adaptive pole placement control

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Interaction Quantification of MTDC Systems Connected with Weak AC Grids

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 2088-2099页

作者： Wanning Zheng Jiabing Hu Li Chai Bing Liu Zixia Sang Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan University of Science and TechnologyWuhan 430081China State Key Laboratory of Advanced Electromagnetic Engineering and Technology and School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China State Grid Hubei Economic Research Institute Wuhan 430077China

The small-signal stability of multi-terminal high voltage direct current(HVDC)systems has become one of the vital issues in modern power *** among voltage source converters(VSCs)have a significant impact on the stability of the *** paper proposes an interaction quantification method based on the self-/en-stabilizing coefficients of the general N-terminal HVDC system with a weak AC network ***,we derive the explicit formulae of self-/en-stabilizing coefficients for any N-terminal HVDC system,which can quantify the interactions through different paths *** relation between the self-/en-stabilizing coefficients and the poles of the system can be used to evaluate the impact of the interactions on the system stability ***,we employ the obtained formulae to analyze the parameter sensitivity and explain how a parameter affects the stability of the system through different paths of ***,extensive examples are given to demonstrate the effectiveness of the proposed method.

关键词： Interactions multi-terminal HVDC self-/enstabilizing coefficients small-signal stability

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Position Regulation of Industrial Robots via Bounded Integral Terminal Sliding Mode control Algorithm

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IEEE Transactions on Industrial Electronics 2024年第7期71卷 7403-7412页

作者： Cong, Yongzheng Du, Haibo Zhu, Wenwu Chen, Chih-Chiang Hefei University of Technology School of Electrical Engineering and Automation Hefei230009 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

For the position regulation problem of six degrees of freedom (6-DOF) industrial robots, a novel bounded finite-time position regulate algorithm is developed and employed to improve the dynamic performance of the industrial robots. First, based on the model feature, a bounded finite-time position regulate law is proposed to overcome input saturation constraints for the considered systems. Rigorous analysis guarantees the finite-time stability of the closed-loop system in the absence of disturbance. Then, to improve the disturbance rejection property of the robot systems in the presence of disturbance, an improved bounded finite-time control law based on the integral terminal sliding mode is constructed. Finally, simulations and experimental results are provided to show the effectiveness of the proposed bounded control law. © 1982-2012 IEEE.

关键词： Asymptotic stability

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Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： Ke Li Shunyi Zhao Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally *** paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear *** high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense *** that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state ***,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing *** results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： filtering estimation error

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Polyphonic sound event localization and detection based on Multiple Attention Fusion ResNet

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Mathematical Biosciences and engineering 2024年第2期21卷 2004-2023页

作者： Zhang, Shouming Zhang, Yaling Liao, Yixiao Pang, Kunkun Wan, Zhiyong Zhou, Songbin Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Intelligent Manufacturing Guangdong Academy of Science Guangdong Key Laboratory of Modern Control Technology Guangzhou510030 China

Sound event localization and detection have been applied in various fields. Due to the polyphony and noise interference, it becomes challenging to accurately predict the sound event and their occurrence locations. Aiming at this problem, we propose a Multiple Attention Fusion ResNet, which uses ResNet34 as the base network. Given the situation that the sound duration is not fixed, and there are multiple polyphonic and noise, we introduce the Gated Channel Transform to enhance the residual basic block. This enables the model to capture contextual information, evaluate channel weights, and reduce the interference caused by polyphony and noise. Furthermore, Split Attention is introduced to the model for capturing cross-channel information, which enhances the ability to distinguish the polyphony. Finally, Coordinate Attention is introduced to the model so that the model can focus on both the channel information and spatial location information of sound events. Experiments were conducted on two different datasets, TAU-NIGENS Spatial Sound Events 2020, and TAU-NIGENS Spatial Sound Events 2021. The results demonstrate that the proposed model significantly outperforms state-of-the-art methods under multiple polyphonic and noise-directional interference environments and it achieves competitive performance under a single polyphonic environment. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License.

关键词： Deep learning

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