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Cascade Optimization Control of Unmanned Vehicle Path Tracking Under Harsh Driving Conditions

Journal of Shanghai Jiaotong university(science) 2023年第1期28卷 114-125页

作者：黄迎港罗文广黄丹蓝红莉 School of Electrical and Information Engineering、Guangxi Key Laboratory of Auto Parts and Vehicle Technology Guangxi University of Science and TechnologyLiuzhou 545006GuangxiChina School of Mechanical and Automotive Engineering South China University of TechnologyGuangzhou 510641China

Under ultra-high-speed and harsh conditions,conventional control methods struggle to ensure the path tracking accuracy and driving stability of unmanned vehicles during the turning ***,this study proposes a cascade control to solve this *** on the new vehicle error model that considers vehicle tire sideslip and road curvature,the feedforward-parametric adaptive linear quadratic regulator(LQR)and proportional integral control-based speed-keeping controllers are used to compose the path-tracking cascade optimization controller for unmanned *** improve the adaptability of the unmanned vehicle path-tracking control under harsh driving conditions,the LQR controller parameters are automatically adjusted using a back-propagation neural network,in which the initial weights and thresholds are optimized using the improved grey wolf optimization algorithm according to the driving *** speed-keeping controller reduces the impact on the curve-tracking accuracy under nonlinear vehicle speed ***,a joint model of MATLAB/Simulink and CarSim was established,and simulations show that the proposed control method can achieve stable entry and exit curves at ultra-high speeds for unmanned *** strong wind and ice road conditions,the method exhibits a higher tracking accuracy and is more adaptive and robust to external interference in driving and variable curvature roads than methods such as the feedforward-LQR,preview and pure pursuit controls.

关键词： unmanned vehicles path tracking harsh driving conditions cascade control improved gray wolf optimization algorithm backpropagation neural network

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Improving the ductility and toughness of nano-TiC/AZ61 composite by optimizing bimodal grain microstructure via extrusion speed

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Journal of Magnesium and Alloys 2024年第8期12卷 3264-3280页

作者： Lingling Fan Mingyang Zhou Wulve Lao Yuwenxi Zhang Hajo Dieringa Ying Zeng Yuanding Huang Gaofeng Quan Key Laboratory of Advanced Technologies of Materials Ministry of EducationChengdu 610031China School of Materials Science and Engineering Southwest Jiaotong UniversityChengdu 610031China Institute of Material and Process Design Helmholtz-Zentrum HereonGeesthacht 21502Germany Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu 610213China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China Institute of Metallic Biomaterials Helmholtz-Zentrum HereonGeesthacht 21502Germany

In this study,the nano-TiC/AZ61 composites with different heterogeneous bimodal grain(HBG)structures and uniform structure are obtained by regulating the extrusion *** effect of HBG structure on the mechanical properties of the composites is *** increasing ductility and toughening mechanism of HBG magnesium matrix composites are carefully *** the extrusion speed increases from 0.75 mm/s to 2.5 mm/s or 3.5 mm/s,the microstructure transforms from uniform to HBG *** with Uniform-0.75 mm/s composite,Heterogeneous-3.5 mm/s composite achieves a 116.7%increase in ductility in the plastic deformation stage and almost no reduction in ultimate tensile *** is mainly because the lower plastic deformation inhomogeneity and higher strain hardening due to hetero-deformation induced(HDI)***,Heterogeneous-3.5 mm/s composite achieves a 108.3%increase in toughness compared with the Uniform-0.75 mm/s *** is mainly because coarse grain(CG)bands can capture and blunt cracks,thereby increasing the energy dissipation for crack propagation and improving *** addition,the CG band of the Heterogeneous-3.5 mm/s composite with larger grain size and lower dislocation density is more conducive to obtaining higher strain hardening and superior blunting crack ***,the increased ductility and toughness of the Heterogeneous-3.5 mm/s composite is more significant than that Heterogeneous-2.5 mm/s composite.

关键词： Nano-TiC/AZ61 composite Extrusion speed Heterogeneous bimodal grain structure Increasing ductility mechanism Toughening mechanism

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FEW SHOT FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON CSML 14

FEW SHOT FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON ...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2024

作者： Wu, Minghao Wu, Lifeng Information Engineering College Capital Normal University Beijing China Beijing Key Laboratory of Electronic System Reliability Technology Capital Normal University Beijing China

ISBN: (纸本)9781837242672

Currently, neural network models have seen widespread adoption in the sphere of fault diagnosis. In the training process of the model there are still problems such as high demand for training data and insufficient generalisation of the model under different working conditions. In order to solve the above problems, in this paper, an algorithm named Cosine Annealing-Sgd-Meta-Learning (CSML) is proposed, which combines the cosine annealing method with the principles of stochastic gradient descent meta-learning. The method uses the cosine annealing algorithm to adjust the learning rate in the outer loop so as to better help the meta-learning task to find the initialisation parameters. In the inner loop, the learning rate is updated using the SGD optimisation algorithm and a wide convolutional network is used to improve the model's ability to extract fault information from the meta-task under known operating conditions, and then the basic learner is updated. High diagnostic accuracy was obtained on the Western Reserve University bearing dataset, which verified its feasibility and effectiveness. © The Institution of engineering & technology 2024.

关键词： Stochastic systems

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Trajectory Optimization for Autonomous Driving in Uncertain Environments Integrated with Risk-Based Corridors 27

Trajectory Optimization for Autonomous Driving in Uncertain ...

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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Li, Zheng Wang, Yijing Zuo, Zhiqiang Shi, Yang Zhao, Rui School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System China University of Victoria Department of Mechanical Engineering VictoriaBC Canada

ISBN: (纸本)9798331505929

Lane change maneuvers of autonomous vehicles in a dynamic highway environment suffer from various uncertainties, especially those from unknown kinematics of surrounding vehicles. In this paper, an optimization-based trajectory planning scheme is proposed to reliably generate collision-free lane change references. By an inner approximation of risk contour, the probabilistic constraints under a given risk level can be converted to the deterministic form, and then, the risk-based corridors are constructed. Decoupled longitudinal and lateral states are sequentially optimized in terms of such corridors and the preferentially determined boundaries of merging instant. Finally, the optimal trajectory is selected from all fused candidates via a prescribed cost indicator. Through both numerical examples and validations on the naturalistic human driving dataset, the advantages of our scheme in reducing crash risks are verified from both statistical analysis and case studies. © 2024 IEEE.

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Multimodal Trajectory Prediction for Autonomous Driving on Unstructured Roads Using Deep Convolutional Network

Multimodal Trajectory Prediction for Autonomous Driving on U...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Li, Lei Chen, Zhifa Wang, Jian Zhou, Bin Yu, Guizhen Chen, Xiaoxuan Key Laboratory of Autonomous Transportation Technology for Special Vehicles Ministry of Industry and Information Technology School of Transportation Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9789819639564

Recently, the application of autonomous driving in open-pit mining has garnered increasing attention for achieving safe and efficient mineral transportation. Compared to urban structured roads, unstructured roads in mining sites have uneven boundaries and lack clearly defined lane markings. This leads to a lack of sufficient constraint information for predicting the trajectories of other human-driven vehicles, resulting in higher uncertainty in trajectory prediction problems. A method is proposed to predict multiple possible trajectories and their probabilities of the target vehicle. The surrounding environment and historical trajectories of the target vehicle are encoded as a rasterized image, which is used as input to our deep convolutional network to predict the target vehicle’s multiple possible trajectories. The method underwent offline testing on a dataset specifically designed for autonomous driving scenarios in open-pit mining and was compared and evaluated against physics-based method. The open-source code and data are available at https://***/LLsxyc/mine_motion_prediction. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Open pit mining

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Malicious Traffic Detection with Noise Labels Based on Cross-Modal Consistency

IEEE Networking Letters

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IEEE Networking Letters 2024年第2期6卷 148-151页

作者： Yuan, Qingjun Niu, Weina Wang, Yongjuan Gou, Gaopeng Lu, Bin Henan Key Laboratory of Network Cryptography Technology Zhengzhou450001 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China

To train robust malicious traffic identification models under noisy labeled datasets, a number of learning with noise labels approaches have been introduced, among which parallel training methods have been proved to be effective. Parallel training methods tend to select samples with disagreement to mitigate the risk of self-control degradation. However, it also introduces noisy knowledge into training. In this letter, we try to avoid introducing noisy knowledge by enhancing the consistency of the representations of parallel networks. Meanwhile, the two networks are heterogeneous and introduce information from different modalities, thus mitigating the risk of self-control degradation from multiple perspectives. © 2019 IEEE.

关键词： Feature extraction

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Delayed interference-based broadband optical chaos generation in a mutual coupled RSOA and DFB system

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Optics Letters 2025年第10期50卷 3381-3384页

作者： Qian, Jiahao Jiang, Ning Li, Anran Zhang, Yiqun Xu, Bingjie Huang, Wei Qiu, Kun School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Tianfu Jiangxi Laboratory Chengdu641419 China National Key Laboratory of Security Communication Chengdu610041 China

In this Letter, a delayed interference (DI)-based chaos generation scheme in a mutually coupled system consisting of a reflective semiconductor optical amplifier (RSOA) and a distributed feedback (DFB) semiconductor laser is proposed. We experimentally demonstrate its capability of generating broadband chaos with a large effective bandwidth and a flat power spectrum, and the influences of relevant parameters on the system performance are thoroughly analyzed. Compared to the conventional optical feedback-based chaos generation schemes, the proposed system can simultaneously output two chaotic signals with enhanced bandwidth and high spectral flatness. Moreover, the time-delay signature (TDS) of chaotic signals generated by this configuration is also effectively suppressed. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Semiconductor optical amplifiers

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A Numerical Calculation Algorithm of the Inclination Function Based on the Representation of SO(3) Group

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 137-148页

作者： Yu-xiao Wei Wen-lin Tang Department of Geophysics School of Geology Engineering and GeomaticsChang’An UniversityXi’an710064China Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing100190China

In the determination of the Earth gravity field in satellite geodesy, the inclination functions represent the projection of data observed along the orbital plane of a satellite orbit into the sphere in the terrestial reference frame. The inclination functions in this work is studied from a group theoretical perspective. The inclination functions are proved to generate a representation of the SO(3) group. An orthogonal relation of the inclination functions is derived and some recurrence relations for the inclination functions are given, based on which an algorithm to calculate the inclination functions is proposed.

关键词： SO(3)group inclination function satellite geodesy representation of SO(3)

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design 13

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Hong, Wenjing Chen, Cheng Zhu, Zexuan Tang, Ke Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350308365

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design. © 2024 IEEE.

关键词： Vaccines

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Statistical Model on CRAFT

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Chinese Journal of Electronics 2022年第4期31卷 698-712页

作者： WANG Caibing GUO Hao YE Dingfeng WANG Ping State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Tianjin Aerospace Zhongwei Data System Technology Co. Ltd.

Many cryptanalytic techniques for symmetric-key primitives rely on specific statistical analysis to extract some secrete key information from a large number of known or chosen plaintext-ciphertext pairs. For example, there is a standard statistical model for differential cryptanalysis that determines the success probability and complexity of the attack given some predefined configurations of the attack. In this work, we investigate the differential attack proposed by Guo et al. at Fast Software Encryption Conference 2020 and find that in this attack, the statistical behavior of the counters for key candidates deviate from standard scenarios, where both the correct key and the correct key xor specific difference are expected to receive the largest number of votes. Based on this bimodal behavior, we give three different statistical models for truncated differential distinguisher on CRAFT(a cryptographic algorithm name) for bimodal phenomena. Then, we provide the formulas about the success probability and data complexity for different models under the condition of a fixed threshold value. Also, we verify the validity of our models for bimodal phenomena by experiments on round-reduced of the versions distinguishers on CRAFT. We find that the success probability of theory and experiment are close when we fix the data complexity and threshold value. Finally, we compare the three models using the mathematical tool Matlab and conclude that Model 3 has better performance.

关键词： Differential cryptanalysis Statistical models Success probability Data complexity Bimodal behavior CRAFT Differential fault analysis (DFA) attacks

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