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IEEE Conference on Decision and control

作者： Dejan Milutinović Alexander Von Moll Satyanarayana G. Manyam David W. Casbeer Isaac E. Weintraub Meir Pachter Dept. University of California Santa Cruz Electrical and Computer Engineering Santa Cruz CA USA Control Science Center Aerospace Systems Directorate Air Force Research Laboratory Dayton OH USA DCS Corporation Dayton OH USA Dept. of Electrical Engineering Air Force Institute of TechnologyWright-Patterson AFB OH USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental for leveraging geometric approaches for solving multiple pursuit-evasion scenarios in the plane. Here, we study a pursuit-evasion differential game on a sphere and generalize the planar Apollonius set to the spherical domain. We find that the interception point from the equilibrium strategies can leave the Apollonius set boundary and present a condition to keep the intercept point on the boundary. This condition allows for generalizing planar pursuitevasion strategies to the sphere.

关键词： Geometry Instruments Differential games Games

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Clebpi: Contrastive Learning for Bug Priority Inference

SSRN

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SSRN 2022年

作者： Wang, Wen-Yao Wu, Chen-Hao He, Jie Faculty of Innovation Engineering Macau University of Science and Technology Macau China College of Computer Science and Electronic Engineering Hunan University Hunan Changsha China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Guangxi Wuzhou China

Context: Automated bug priority inference can reduce the time overhead of bug triagers for priority assignments, improving the efficiency of software ***: There are two orthogonal lines for this task, i.e., traditional machine learning based (TML-based) and neural network based (NN based) approaches. Although these approaches achieve competitive performance, our observation finds that existing approaches face the following two issues: 1) TML-based approaches require much manual feature engineering and cannot learn the semantic information of bug reports;2) Both TML-based and NN-based approaches cannot effectively address the label imbalance problem because they are difficult to distinguish the semantic difference between bug reports with different ***: We propose CLeBPI (Contrastive Learning for Bug Priority Inference), which leverages pre-trained language model and contrastive learning to tackle the above-mentioned two issues. Specifically, CLeBPI is first pre-trained on a large-scale bug report corpus in a self-supervised way, thus it can automatically learn contextual representations of bug reports without manual feature engineering. Afterward, it is further pre-trained by a contrastive learning objective, which enables it to distinguish semantic differences between bug reports, learning more precise contextual representations for each bug report. When finishing pre-training, we can connect a classification layer to CLeBPI and fine-tune it for bug priority inference in a supervised ***: We choose four baseline approaches and conduct comparison experiments on a public dataset. The experimental results show that CLeBPI outperforms all baseline approaches by 23.86%-77.80% in terms of weighted average F1-score, showing its ***: This paper proposes CLeBPI, a pre-trained model combining contrastive learning that can automatically predict bug priority. Experimental results show its effectiveness. © 2022, The A

关键词： computer software maintenance

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Equalizer zero-determinant strategy in discounted repeated Stackelberg asymmetric game

arXiv

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arXiv 2023年

作者： Zhaoyang, Cheng Guanpu, Chen Yiguang, Hong Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai210201 China

This paper focuses on the performance of equalizer zero-determinant (ZD) strategies in discounted repeated Stackerberg asymmetric games. In the leader-follower adversarial scenario, the strong Stackelberg equilibrium (SSE) deriving from the opponents’ best response (BR), is technically the optimal strategy for the leader. However, computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of states. To this end, we propose to adopt an equalizer ZD strategy, which can unilaterally restrict the opponent’s expected utility. We 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 strategy. Then we turn to multi-player models, where there exists one player adopting an equalizer ZD strategy. We give bounds of the sum of opponents’ utilities, and compare it with the SSE strategy. Finally, we give simulations on unmanned aerial vehicles (UAVs) and the moving target defense (MTD) to verify the effectiveness of our approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Equalizers

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Sparse Prior Is Not All You Need: When Differential Directionality Meets Saliency Coherence for Infrared Small Target Detection

arXiv

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arXiv 2024年

作者： Zhou, Fei Fu, Maixia Qian, Yulei Yang, Jian Dai, Yimian Ministry of Education Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou China Nanjing Marine Radar Institute Nanjing China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

Infrared small target detection is crucial for the efficacy of infrared search and tracking systems. Current tensor decomposition methods emphasize representing small targets with sparsity but struggle to separate targets from complex backgrounds due to insufficient use of intrinsic directional information and reduced target visibility during decomposition. To address these challenges, this study introduces a Sparse Differential Directionality prior (SDD) framework. SDD leverages the distinct directional characteristics of targets to differentiate them from the background, applying mixed sparse constraints on the differential directional images and continuity difference matrix of the temporal component, both derived from Tucker decomposition. We further enhance target detectability with a saliency coherence strategy that intensifies target contrast against the background during hierarchical decomposition. A Proximal Alternating Minimization-based (PAM) algorithm efficiently solves our proposed model. Experimental results on several real-world datasets validate our method’s effectiveness, outperforming ten state-of-the-art methods in target detection and clutter suppression. Our code is available at https://***/GrokCV/SDD. Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors

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Regulation of Calcium Ions on the Interaction between Amphotericin B and Cholesterol-Rich Phospholipid Monolayer in Le Phase and Lc Phase

SSRN

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SSRN 2023年

作者： Wang, Juan Sheng, Qingqing Feng, Shun Wang, Zhen Shaanxi Engineering Research Center of Controllable Neutron Source School of Electronic Information Xijing University Xi’an710123 China Xi’an Key Laboratory of Human-Machine Integration and Control Technology for Intelligent Rehabilitation School of Computer Science Xijing University Xi’an710123 China

Amphotericin B, as a "gold standard", is used to treat invasive fungal infections. The AmB molecule can bind easily to cholesterol and damage cell membranes, so it produces the toxicity on cell membrane, which limits its clinical dose. However, the interaction between AmB and cholesterol-rich membrane is unclear now. The phase state of the membrane and the metal cation outside cell membrane may affect the interaction between AmB and the membrane. In this work, the effects of amphotericin B on the mean molecular area, elastic modulus and stability of mammalian cell membrane rich in cholesterol in the presence of Ca2+ ions were studied using DPPC/Chol mixed Langmuir monolayer as a model. The Langmuir-Blodgett method and AFM test were used to study the effects of this drug on the morphology and height of cholesterol-rich phospholipid membrane in the presence of Ca2+ ions. The influence of calcium ions on the mean molecular area and the limiting molecular area was similar in LE phase and in LC phase. The calcium ions made the monolayer more condensed. However, calcium ions can weaken the shortening effect of AmB on the relaxation time of the DPPC/Chol mixed monolayer in LE phase but enhance it in LC phase. Interestingly, calcium ions caused a LE-LC coexistence phase to occur in the DPPC/Chol/AmB mixed monolayers at 35mN/m, which was confirmed by atomic force microscopy. The results can help to understand the interaction between amphotericin B and cell membrane rich in cholesterol in the calcium ions environment. © 2023, The Authors. All rights reserved.

关键词： Cholesterol

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Over-the-air computation via reconfigurable intelligent surface

arXiv

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arXiv 2021年

作者： Fang, Wenzhi Jiang, Yuning Shi, Yuanming Zhou, Yong Chen, Wei Letaief, Khaled B. The School of Information Science and Technology ShanghaiTech University Shanghai201210 China Automatic Control Laboratory EPFL Switzerland The Department of Electronic Engineering Tsinghua University Beijing100084 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels. However, the performance of AirComp is bottlenecked by the worst channel condition among all links between the IoT devices and the access point. In this paper, a reconfigurable intelligent surface (RIS) assisted AirComp system is proposed to boost the received signal power and thus mitigate the performance bottleneck by reconfiguring the propagation channels. With an objective to minimize the AirComp distortion, we propose a joint design of AirComp transceivers and RIS phase-shifts, which however turns out to be a highly intractable non-convex programming problem. To this end, we develop a novel alternating minimization framework in conjunction with the successive convex approximation technique, which is proved to converge monotonically. To reduce the computational complexity, we transform the subproblem in each alternation as a smooth convex-concave saddle point problem, which is then tackled by proposing a Mirror-Prox method that only involves a sequence of closed-form updates. Simulations show that the computation time of the proposed algorithm can be two orders of magnitude smaller than that of the state-of-the-art algorithms, while achieving a similar distortion performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Mirrors

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Artificial Neural Network-Based Direct Power control to Enhance the Performance of a Pmsg-Wind Energy Conversion System Under Real Wind Speed and Parameter Uncertainties: An Experimental Validation

SSRN

引用

SSRN 2023年

作者： Majout, Btissam Bossoufi, Badre Karim, Mohammed Skruch, Pawel Mobayen, Saleh El Mourabit, Youness El Zair Laggoun, Zakaria Laboratory of Engineering Modelling and Systems Analysis SMBA University Fez Morocco Department of Automatic Control and Robotics AGH University of Science and Technology Kraków30-059 Poland Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan National School of Applied Sciences Abdelmalek Essaadi University Tetouan Morocco Laboratory of Electrotechnique Constantine Mentouri Brothers Constantine 1 University Constantine Algeria

With the increasing emphasis on embedding advanced technology into system controls, the Direct Power control (DPC) approach has garnered significant attention, owing to its straightforward and highly adaptable algorithm. It has been adopted in many applications. However, the variable frequency, harmonic distortion of the currents, and power ripples caused by Hysteresis controllers and switching tables decrease its effectiveness and robustness, affecting the system’s performance. For this reason, this paper proposed a new DPC based on Artificial Neural Network (ANN) approaches. In this approach, the hysteresis comparator and the switching table are substituted with ANN controllers and then applied on both sides: machine-side converter (MSC) and grid-side converter (GSC) of a Permanent Magnet Synchronous Generator based Wind Energy Conversion System (PMSG-WECS). Moreover, to make the system more efficient in varying wind conditions, this study expands the utilization of the artificial neural networks (ANN) to encompass the maximum power point tracking (MPPT) control strategy. To demonstrate the effectiveness of the proposed approach on the system behaviors, a simulation test was carried out in the Matlab/Simulink environment, using a real wind profile of a Moroccan city (Essaouira). In comparison to the classical DPC control, the simulation results showed the superior performance of the proposed ANN-DPC control in terms of reference tracking, response time, overshoot, precision, and its capacity to reduce the rate of power ripples and total harmonic distortion (THD) in the injected currents. Furthermore, a robustness test was also included in this work to check the robustness of the proposed control against parameters variation. In conclusion, the feasibility and effectiveness of the ANN-DPC control approach were confirmed through experimental validation using the dSPACE DS1104 board. © 2023, The Authors. All rights reserved.

关键词： MATLAB

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Fatigue Life Analysis of Piezoelectric Actuating Mechanism with Micro-displacement Amplifier

Fatigue Life Analysis of Piezoelectric Actuating Mechanism w...

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xinyuan Zhang Shaoping Wang Xiao Wu Siyuan He Xingjian Wang Yu Niu Alex I. Gavrilov School of Automation Science and Electrical Engineering Beihang University Beijing China Tianmushan Laboratory Xixi Octagon City China Ningbo Institute of Technology Beihang University Ningbo China Research Institute of Aero-Engine Beihang University Beijing China Department of Automatic Control Systems Bauman Moscow State Technical University Moscow Russia

Since piezoelectric actuating mechanism generally operate in high frequency response state, fatigue life has become an important factor influencing the performance and reliability of the entire drive mechanism. In order to investigate whether the designed piezoelectric ceramic actuator meets the active control requirements of the aero-engine, the paper analyzes the fatigue characteristics and fatigue life of the piezoelectric ceramic materials and the micro displacement amplification mechanism with finite element analysis softwareˈ and the optimal spacing value is obtained by studying the effect of the flexible hinge spacing on the fatigue characteristics of the displacement amplifier. And then, the fatigue life of the displacement amplifier is analyzed based on the drive load spectrum of the aircraft during simulated flight, whose result is 340.93 hours. Finally, the fatigue life of the piezoelectric actuating mechanism is 32 minutes when loaded with full power, which meets the design target initially.

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Cache-Assisted Content Delivery for NOMA-Based Satellite-Edge-Terminal Cooperation Networks

Cache-Assisted Content Delivery for NOMA-Based Satellite-Edg...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Chao Fang Hang Xu Yingshan Li Haofei Xie Shu-Ming Tseng Zheng Yang Deze Zeng Faculty of Information Technology Beijing University of Technology Beijing China Purple Mountain Laboratories Nanjing China Key Laboratory of Industrial Internet of Things & Networked Control Chongqing University of Posts and Telecommunications Chongqing China Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Normal University Fuzhou China School of Computer Science China University of Geosciences Wuhan China

To satisfy differentiated service requirements of delay-sensitive and computing-intensive tasks in satellite communication networks, we propose a cache-assisted low-latency content distribution scheme in multi-cell multi-carrier nonorthogonal multiple access (MCMC-NOMA)-based satellite-edge-terminal cooperation environments. In the paper, a delay minimization problem is formulated to achieve optimal content distribution by jointly optimizing the allocation of subchannels and transmit power, which is decomposed and solved in each slot by using many-to-one matching and successive convex approximation, respectively. Simulation results show that the proposed model significantly improve network latency and content distribution in comparison to its existing counterparts in cloud-edge-terminal cooperation networks.

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Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming

引用

IFAC-PapersOnLine 2021年第7期54卷 379-384页

作者： Ştefan-Cristian Nechita Roland Tóth Dhruv Khandelwal Maarten Schoukens Department of Electrical Engineering Eindhoven University of Technology Eindhoven University of Technology Eindhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 H-1111 Budapest Hungary

Data-driven modeling of nonlinear dynamical systems often requires an expert user to take critical decisions a priori to the identification procedure. Recently, an automated strategy for data driven modeling of single-input single-output (SISO) nonlinear dynamical systems based on genetic programming (GP) and tree adjoining grammars (TAG) was introduced. The current paper extends these latest findings by proposing a multi-input multi-output (MIMO) TAG modeling framework for polynomial NARMAX models. Moreover, we introduce a TAG identification toolbox in Matlab that provides implementation of the proposed methodology to solve multi-input multi-output identification problems under NARMAX noise assumption. The capabilities of the toolbox and the modeling methodology are demonstrated in the identification of two SISO and one MIMO nonlinear dynamical benchmark models.

关键词： Nonlinear system identification Equation discovery Tree Adjoining Grammar Genetic Programming Data-driven system modeling

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