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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wang, Miaomiao Sun, Zhendong Academy of Mathematics and Systems Science Chinese Academy of Sciences Key Laboratory of Systems and Control Beijing100190 China Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao266590 China

ISBN: (纸本)9798350316339

Given a switched system and a safe region that is a subset of the state space, a state trajectory is safe if the whole trajectory is within the safe region. The safety-critical stability problem here is to determine the safe initial domain that is the set of initial states with safe trajectories under arbitrary switching. We prove that the safe initial domain is of full dimension iff the switched system is stable. Moreover, under the assumption that the switched system is exponentially stable and the safe region is regular, we present a computational procedure to numerically characterize the safe initial domain with the help of the newly introduced concept of 'cut-tail-points'. A numerical example is presented to verify the effectiveness of the proposed scheme. © 2024 IEEE.

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Active electronic skin:an interface towards ambient haptic feedback on physical surfaces

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npj Flexible Electronics 2024年第1期8卷 684-710页

作者： Yuan Guo Yun Wang Qianqian Tong Boxue Shan Liwen He Yuru Zhang Dangxiao Wang State Key Lab of Virtual Reality Technology and Systems BeijingChina School of Mechanical Engineering and Automation Beihang UniversityBeijingChina Department of Strategic and Advanced Interdisciplinary Research Peng Cheng LaboratoryShenzhenChina

In the era of ubiquitous computing with flourished visual displays in our surroundings,the application of haptic feedback technology still remains in its *** the gap between haptic technology and the real world to enableambient haptic feedback on various physical surfaces is a grand challenge in the field of human-computer *** paper presents the concept of an active electronic skin,characterized by three features:richness(multi-modal haptic stimuli),interactivity(bi-directional sensing and actuation capabilities),and invisibility(transparent,ultra-thin,flexible,and stretchable).By deploying this skin on physical surfaces,dynamic and versatile multi-modal haptic display,as well as tactile sensing,can be *** potential applications of this skin include two categories:skin for the physical world(such as intelligent home,intelligent car,and intelligent museum),and skin for the digital world(such as haptic screen,wearable device,and bare-hand device).Furthermore,existing skin-based haptic display technologies including texture,thermal,and vibrotactile feedback are surveyed,as well as multidimensional tactile sensing *** analyzing the gaps between current technologies and the goal of ambient haptics,future research topics are proposed,encompassing fundamental theoretical research on the physiological and psychological perception mechanisms of human skin,spatial-temporal registration among multimodal haptic stimuli,integration between sensing and actuation,and spatial-temporal registration between visual and haptic *** concept of active electronic skin is promising for advancing the field of ambient haptics,enabling seamless integration of touch into our digital and physical surroundings.

关键词： Active ambient electronic

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Equalizer Zero-Determinant Strategy in Discounted Repeated Stackelberg Asymmetric Game

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Journal of systems Science & Complexity 2024年第1期37卷 184-203页

作者： CHENG Zhaoyang CHEN Guanpu HONG Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology10044 StockholmSweden. Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 210201China

This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.

关键词： Discounted repeated Stackelberg asymmetric game equalizer zero-determinant strategy strong Stackelberg equilibrium strategy

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Exchange Strategies for Multi-Colony Ant Algorithms in Dynamic Environments 13

Exchange Strategies for Multi-Colony Ant Algorithms in Dynam...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mavrovouniotis, Michalis Li, Changhe Yazdani, Danial Handjimitsis, Diofantos Eratosthenes Centre of Excellence Limassol Cyprus Cyprus University of Technology Department of Civil Engineering and Geomatics Limassol Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China University of Technology Sydney Faculty of Engineering & Information Technology Sydney Australia

ISBN: (纸本)9798350308365

In dynamic optimization problems where optimal solutions change over time, traditional ant colony optimization (ACO) algorithms face limitations. This study explores the adaptation of multi-colony ACO algorithms, known for their enhanced search capabilities in stationary problems, to tackle optimization problems in dynamic environments. Various strategies for exchanging information between colonies, which is a critical factor influencing algorithm performance, are investigated. Using the dynamic traveling salesman problem as a foundation, we generate test cases to reflect real-world complexities. Our results on a set of problem instances reveal that the choice of communication strategy between colonies significantly impacts the adaptability and efficiency of multi-colony ACO algorithms in tracking moving optimum. © 2024 IEEE.

关键词： Ant colony optimization

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Online Residual Learning from Offline Experts for Pedestrian Tracking 63

Online Residual Learning from Offline Experts for Pedestrian...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Vlachos, Anastasios Tsiamis, Anastasios Karapetyan, Aren Balta, Efe C. Lygeros, John Eth Zürich Automatic Control Laboratory Department of Information Technology and Electrical Engineering Zürich8092 Switzerland Control and Automation Group Inspire ZürichAG 8005 Switzerland The Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350316339

In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-trained predictions. At a lower level, we employ multiple offline predictions generated before or at the beginning of the prediction horizon. We augment every offline prediction by learning their respective residual error concerning the true target state online, using the recursive least squares algorithm. At a higher level, we treat the augmented lower-level predictors as experts, adopting the Prediction with Expert Advice framework. We utilize an adaptive softmax weighting scheme to form an aggregate prediction and provide guarantees for ORL in terms of regret. We employ ORL to boost performance in the setting of online pedestrian trajectory prediction. Based on data from the Stanford Drone Dataset, we show that ORL can demonstrate best-of-both-worlds performance. © 2024 IEEE.

关键词： Prediction models

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Data-Driven Tracking control of a Cushion Robot with Safe Autonomous Motion Considering Human-Machine Interaction Environment

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Journal of Dynamic systems, Measurement and control 2025年第4期147卷 041003页

作者： Sun, Ping Shan, Rui Chang, Hongbin Wang, Shuoyu School of Artificial Intelligence Shenyang University of Technology Shenyang110870 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110169 China Department of Intelligent Mechanical Systems Engineering Kochi University of Technology Kochi7828502 Japan

This study proposes a data-driven safety controller with velocity constraints for a cushion robot. We constructed a mathematical description of the human-machine interaction environment by decomposing the generalized input force and coefficient matrix in the dynamic model. We established a new equivalent data model, which considered various human-machine interaction environments using a pseudo-Jacobian matrix. A stochastic configuration network (SCN) estimation method for variations in the human-machine interaction environment was proposed, with hidden layer nodes added at random. We designed a safe autonomous navigation path and proposed a data-driven control method that limited the actual velocity while stabilizing the tracking error system. In addition, the desired motion velocity of the robot was designed. This approach has the advantage of ensuring safety at a specified velocity. We also demonstrated and validated the effectiveness of the proposed data-driven algorithm using simulation-based comparative analysis and an experimental study. Copyright © 2024 by ASME.

关键词： Stochastic systems

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Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1822-1833页

作者： Wei Xu Chen Zhao Jie Cheng Yin Wang Yiqing Tang Tao Zhang Zhiming Yuan Yisheng Lv Fei-Yue Wang Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Signal&Communication Research Institute China Academy Railway SciencesBeijing 100081China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway *** such cases,train timetables need to be ***,timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization *** paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based ***,the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer,providing the better understanding of overall operation in the high-speed railway ***,a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast *** experiments on various delay scenarios are *** results demonstrate the effectiveness of the proposed method in comparison to other popular methods.

关键词： High-speed railway reinforcement learning train timetable rescheduling Transformer

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CDQKL: Consensus-Based Distributed Quantum Kernel Learning 1

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Ma, Wenxuan Liu, Mengxiang Deng, Ruilong State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou310027 China University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350366778

The field of quantum computing has developed rapidly in recent years due to its promising trend of surpassing traditional machine learning in terms of speed and effectiveness. Quantum kernel learning is one of the paradigms of quantum machine learning, but the training of quantum kernel is time consuming. Therefore, this work makes the first attempt to introduce a consensus-based distributed approach to quantum kernel learning - named CDQKL - that only requires to exchange model parameter information between adjacent nodes while avoiding the need of sharing local training data. Through comparative experimental studies, the advantages of CDQKL in classification accuracy and convergence speed are verified. Considering the popularization of quantum computing cloud service and miniaturization of quantum terminals, the CDQKL adapting to this trend is able to play a vital role in data security, which implies the far-reaching significance of this work. Our code is available at https://***/Leisurivan/CDOKL. © 2024 IEEE.

关键词： Quantum computers

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An aircraft brake control algorithm with torque compensation based on RBF neural network

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Chinese Journal of Aeronautics 2024年第1期37卷 438-450页

作者： Ning BAI Xiaochao LIU Juefei LI Zhuangzhuang WANG Pengyuan QI Yaoxing SHANG Zongxia JIAO School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100191China Key Laboratory of Advanced Aircraft Systems(Beihang University) Ministry of Industry and Information TechnologyBeijing 100091China Research Institute for Frontier Science Beihang UniversityBeijing 100191China Ningbo Institute of Technology of Beihang University Ningbo 315800China Tianmushan Laboratory Xixi Octagon CityYuhang DistrictHangzhou 310023China

The wheel brake system of an aircraft is the key to ensure its safe landing and rejected takeoff.A wheel’s slip state is determined by the brake torque and ground adhesion torque,both of which have a large degree of *** is this nature that brings upon the challenge of obtaining high deceleration rate for aircraft brake *** overcome the disturbances caused by the above uncertainties,a braking control law is designed,which consists of two parts:runway surface recognition and wheel’s slip state *** runway surface recognition,the identification rules balancing safety and braking efficiency are defined,and the actual identification process is realized through recursive least square method with forgetting *** slip state tracking,the LuGre model with parameter adaptation and a brake torque compensation method based on RBF neural network are proposed,and their convergence are *** effectiveness of our control law is verified through simulation and ground *** in the experiments on the ground inertial test bench,compared to the improved pressure-biased-modulation(PBM)anti-skid algorithm,fewer wheel slips occur,and the average deceleration rate is increased by 5.78%,which makes it a control strategy with potential for engineering applications.

关键词： Aircraft landing Brakes Disturbance observer Neural networks Runway identification

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