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arXiv 2021年

作者： Chen, Guanpu Li, Weijian Xu, Gehui Hong, Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Automation University of Science and Technology of China Anhui Hefei China Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

To solve distributed optimization efficiently with various constraints and nonsmooth functions, we propose a distributed mirror descent algorithm with embedded Bregman damping, as a generalization of conventional distributed projection-based algorithms. In fact, our continuous-time algorithm well inherits good capabilities of mirror descent approaches to rapidly compute explicit solutions to the problems with some specific constraint structures. Moreover, we rigorously prove the convergence of our algorithm, along with the boundedness of the trajectory and the accuracy of the solution. © 2021, CC0.

关键词： Mirrors

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An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise

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Sensors (Basel, Switzerland) 2025年第10期25卷 3130页

作者： Di Deng Peng Yi Junlin Xiong Department of Control Science and Engineering Tongji University Shanghai 201804 China. Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 201210 China. Department of Automation University of Science and Technology of China Hefei 230026 China.

Event-triggered state estimation has attracted significant attention due to the advantage of efficiently utilizing communication resources in wireless sensor networks. In this paper, an adaptive robust event-triggered variational Bayesian filtering method is designed for heavy-tailed noise with inaccurate nominal covariance matrices. The one-step state prediction probability density function and the measurement likelihood function are modeled as Student's t-distributions. By choosing inverse Wishart priors, the system state, the prediction error covariance, and the measurement noise covariance are jointly estimated based on the variational Bayesian inference and the fixed-point iteration. In the proposed filtering algorithm, the system states and the unknown covariances are adaptively updated by taking advantage of the event-triggered probabilistic information and the transmitted measurement data in the cases of non-transmission and transmission, respectively. The tracking simulations show that the proposed filtering method achieves good and robust estimation performance with low communication overhead.

关键词： event-triggered scheduling scheme non-Gaussian noise robust state estimation variational Bayesian approach

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EDOLAB: An Open-Source Platform for Education and Experimentation with Evolutionary Dynamic Optimization Algorithms

arXiv

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arXiv 2023年

作者： Peng, Mai Yazdani, Delaram She, Zeneng Yazdani, Danial Luo, Wenjian Li, Changhe Branke, Juergen Nguyen, Trung Thanh Gandomi, Amir H. Yang, Shengxiang Jin, Yaochu Yao, Xin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Research Institute Faculty of Engineering and Technology Liverpool John Moores University United Kingdom School of Computer Science and Technology Harbin Institute of Technology China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies School of Computer Science and Technology Harbin Institute of Technology Peng Cheng Laboratory China School of Artificial Intelligence Anhui University of Sciences & Technology China Information Systems Management and Analytics in Warwick Business School University of Warwick United Kingdom Faculty of Engineering & Information Technology University of Technology Sydney Australia Obuda University Hungary School of Computer Science and Informatics De Montfort University United Kingdom Department of Artificial Intelligence School of Engineering Westlake University China School of Computer Science University of Birmingham United Kingdom

Many real-world optimization problems exhibit dynamic characteristics, posing significant challenges for traditional optimization techniques. Evolutionary Dynamic Optimization Algorithms (EDOAs) are designed to address these challenges effectively. However, in existing literature, the reported results for a given EDOA can vary significantly. This inconsistency often arises because the source codes for many EDOAs, which are typically complex, have not been made publicly available, leading to error-prone re-implementations. To support researchers in conducting experiments and comparing their algorithms with various EDOAs, we have developed an open-source MATLAB platform called the Evolutionary Dynamic Optimization LABoratory (EDOLAB). This platform not only facilitates research but also includes an educational module designed for instructional purposes. The education module allows users to observe: a) a 2-dimensional problem space and its morphological changes following each environmental change, b) the behaviors of individuals over time, and c) how the EDOA responds to environmental changes and tracks the moving optimum. The current version of EDOLAB features 25 EDOAs and four fully parametric benchmark generators. © 2023, CC BY-NC-SA.

关键词： Optimization algorithms

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Parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

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Exact Differentiator with Lipschitz Continuous Output and Optimal Worst-Case Accuracy Under Bounded Noise

Exact Differentiator with Lipschitz Continuous Output and Op...

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IEEE Conference on Decision and control

作者： Rodrigo Aldana-López Richard Seeber Hernan Haimovich David Gómez-Gutiérrez Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza Spain Christian Doppler Laboratory for Model Based Control of Complex Test Bed Systems Institute of Automation and Control Graz University of Technology Graz Austria Centro Internacional Franco-Argentino de Ciencias de la Información y de Sistemas (CIFASIS) CONICET-UNR Rosario Argentina Intel Tecnología de México Intel Labs Intelligent Systems Research Lab Jalisco Mexico Tecnológico Nacional de México Instituto Tecnológico José Mario Molina Pasquel y Henríquez Unidad Académica Zapopan Jalisco Mexico

The online differentiation of a signal contaminated with bounded noise is addressed. A differentiator is developed that generates a Lipschitz continuous output, is exact in the absence of noise, and provides the optimal worst-case accuracy among all possible exact differentiators when noise is present. This combination of features is not shared by any previously existing differentiator. Tuning of the developed differentiator is very simple, requiring only the knowledge of a bound for the second-order derivative of the signal. The approach consists in regularizing the possibly highly noisy output of a recently introduced linear adaptive robust exact differentiator and feeding it to a first-order sliding-mode filter designed to maintain optimal accuracy. The proposed regularization and filtering of this output allows trading the speed with which exactness is obtained for the feature of a Lipschitz continuous, hence less noisy, output. An illustrative example is provided to highlight the features of the developed differentiator.

关键词：

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Input Constrained Prescribed Performance-Based control for Hypersonic Gliding Vehicle

SSRN

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SSRN 2025年

作者： Zheng, Kefan Zhao, Xinyue Zeng, Xianlin Zhang, Xiaozhen Fang, Hao Hong, Yiguang National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing100081 China School of Automation Beijing Institute of Technology Beijing100081 China Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China Department of Control Science and Engineering Tongji University Shanghai200092 China

This paper proposes an input constrained prescribed performance-based control (IC-PPC) scheme to investigate the tracking control problem of hypersonic glide vehicle (HGV) system simultaneously considering the user-specified tracking performance and control input constraints. To overcome the challenges caused by the high nonlinearity of the aerodynamic coefficients, the dynamic of HGV system is transformed into the strict-feedback form through the introduction of virtual inputs. A novel decoupling method is developed for the separation of the non-convex coupling constraints of virtual inputs and the calculation of the input saturation errors (the errors between actual and desired inputs). To avoid the violation of the user-specified tracking performance due to the input saturation, an auxiliary system is developed to generate the modified signals. These signals are guaranteed to be non-negative and used to create the input constrained performance functions (IC-PFs), which are capable to degrade or recover the performance boundaries depending on different saturation conditions. Consequently, it is theoretically shown that the output can always track the desired trajectories and satisfy the constraints of the IC-PFs. Finally, comparative simulations are presented to showcase these theoretical findings. © 2025, The Authors. All rights reserved.

关键词： Three term control systems

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Privacy-Preserving Brain-Computer Interfaces: A Systematic Review

arXiv

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arXiv 2024年

作者： Xia, Kun Duch, Wlodzislaw Sun, Yu Xu, Kedi Fang, Weili Luo, Hanbin Zhang, Yi Sang, Dong Xu, Xiaodong Wang, Fei-Yue Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Zhejiang Lab Hangzhou311121 China The Department of Informatics School of Physics Astronomy and Informatics Neurocognitive Laboratory Center for Modern Interdisciplinary Technologies Nicolaus Copernicus University Torun Poland The Ministry of Education Key Laboratory for Biomedical Engineering Zhejiang University Hangzhou China The Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou China Department of Biomedical Engineering Zhejiang University Hangzhou China The School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China The College of Public Administration Huazhong University of Science and Technology Wuhan430074 China The NetsUnion Clearing Corporation Beijing100045 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100049 China

A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most research so far focuses on making BCIs more accurate and reliable, but much less attention has been paid to their privacy. Developing a commercial BCI system usually requires close collaborations among multiple organizations, e.g., hospitals, universities, and/or companies. Input data in BCIs, e.g., electroencephalogram (EEG), contain rich privacy information, and the developed machine learning model is usually proprietary. Data and model transmission among different parties may incur significant privacy threats, and hence privacy protection in BCIs must be considered. Unfortunately, there does not exist any contemporary and comprehensive review on privacy-preserving BCIs. This paper fills this gap, by describing potential privacy threats and protection strategies in BCIs. It also points out several challenges and future research directions in developing privacy-preserving BCIs. © 2024, CC BY.

关键词： Differential privacy

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Weipeng Cao Xuyang Yao Zhiwu Xu Yinghui Pan Yixuan Sun Dachuan Li Bohua Qiu Muheng Wei Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen) Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.

关键词： Visualization Adaptation models Semantics Zero shot learning Neural networks Termination of employment Transformers Market research Sun Optimization

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Space Charge Transport of $\boldsymbol{\text{Al}_2 \mathrm{O}_3}$ /Silicone Rubber Composites Under Thermal Aging

Space Charge Transport of $\boldsymbol{\text{Al}_2 \mathrm{O...

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International Conference on High Voltage engineering and Application, ICHVE

作者： Yunxiao Zhang Chenning Yan Kai Wu Yuanxiang Zhou Tianfeng Zhang College of Electrical Engineering and Automation Fuzhou University Fuzhou Fujian China Department of Electrical Engineering State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China The Wind Solar Storage Division of State Key Laboratory of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi China Electric Power Research Institute Anhui Electric Power Company of State Grid Hefei China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407519

Silicone rubber (SIR) has been widely used in the insulation of cable accessories due to its excellent performance. In this paper, pure SIR and nano $\boldsymbol{\text{Al}_2 \mathrm{O}_3 / \text{SIR}}$ composites are thermally aged for 0–80 days at $\boldsymbol{200^{\circ} \mathrm{C}}$ . The effects of long-term thermal aging on the space charge transport are analyzed. The results show that with the increase of thermal aging time, the accumulation of heteropolar charge of pure SIR and nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites gradually decreases and changes to the accumulation of homopolar charge. Compared with pure SIR, the space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites decreases significantly and changes little with the increase of thermal aging time. It is believed that when doped nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}}$ in SIR, the increase of carrier mobility and the introduction of metal oxides reacting with fallen free radicals to form stable compounds both lead to less space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites.

关键词： Nanocomposites Impurities Metals High-voltage techniques Aging Space charge Thermal analysis

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Localization of Chiral Edge States by the Non-Hermitian Skin Effect

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Physical Review Letters 2024年第11期132卷 113802-113802页

作者： Gui-Geng Liu (刘癸庚) Subhaskar Mandal Peiheng Zhou Xiang Xi Rimi Banerjee Yuan-Hang Hu Minggui Wei Maoren Wang Qiang Wang Zhen Gao Hongsheng Chen Yihao Yang Yidong Chong Baile Zhang Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore 637371 Singapore National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu 610054 China School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan 523808 China School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing Jiangsu 210093 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen 518055 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang ZJU-UIUC Institute Zhejiang University Hangzhou 310027 China Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore

Quantum Hall systems host chiral edge states extending along the one-dimensional boundary of any two-dimensional sample. In solid state materials, the edge states serve as perfectly robust transport channels that produce a quantized Hall conductance; due to their chirality, and the topological protection by the Chern number of the bulk band structure, they cannot be spatially localized by defects or disorder. Here, we show experimentally that the chiral edge states of a lossy quantum Hall system can be localized. In a gyromagnetic photonic crystal exhibiting the quantum Hall topological phase, an appropriately structured loss configuration imparts the edge states’ complex energy spectrum with a feature known as point-gap winding. This intrinsically non-Hermitian topological invariant is distinct from the Chern number invariant of the bulk (which remains intact) and induces mode localization via the “non-Hermitian skin effect.” The interplay of the two topological phenomena—the Chern number and point-gap winding—gives rise to a non-Hermitian generalization of the paradigmatic Chern-type bulk-boundary correspondence principle. Compared to previous realizations of the non-Hermitian skin effect, the skin modes in this system have superior robustness against local defects and disorders.

关键词： Edge states Photonic crystals Quantum Hall effect Chern insulators Non-Hermitian systems

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