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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Long, Changqing Meng, Wenchao Zhang, Yongmin College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China School of Computer and Engineering Central South University Changsha410083 China

ISBN: (纸本)9798350325959

Mobile edge computing (MEC) can extend computing power at the edge of wireless networks by migrating compute-intensive tasks to MEC servers, which has the potential to enable compute-intensive applications in 5G networks. However, whether to offload tasks and how much edge computing resources to allocate to it is an NP-hard problem. In this paper, a MEC system enabled multi-user wireless network is proposed, in which the access point (AP) is equipped with a MEC server that provides computing resources for mobile users through task offloading. Then, the issue of task offloading and resource allocation is formulated as a mixed integer nonlinear program to minimize the overhead of the entire MEC system, represented by a weighted sum of delay and energy consumption. Furthermore, a collaborative neurodynamic optimization (CNO) with levy mutation operator (CNO-LMO) algorithm is proposed for searching global optimal solutions to the formulated problem. Finally, the experimental results are given to verify the superiority of the proposed CNO-LMO in reducing the overhead of the MEC system compared to some other algorithms. © 2023 IEEE.

关键词： collaborative neurodynamic optimization (CNO) mixed integer nonlinear program (MINLP) mobile edge computing (MEC) resource allocation task offloading

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Design of Distribution Tariffs for Energy Hub Networks to Reduce Carbon Emissions

Design of Distribution Tariffs for Energy Hub Networks to Re...

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European control Conference (ECC)

作者： Varsha Behrunani Federica Bellizio Philipp Heer John Lygeros Automatic Control Laboratory ETH Zurich Switzerland Urban Energy Systems Laboratory Swiss Federal Institute of Material Science and Technology Empa Switzerland Urban Energy Eystems Laboratory Swiss Federal Institute of Material Science and Technology Empa Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Utilizing demand-side flexibility provides a viable, cost-efficient and low-carbon alternative to standard grid reinforcement. Energy hubs can provide such a flexibility by leveraging both electrical and thermal grids. This work proposes a novel pricing model for distribution tariffs to fulfill network-wide objectives, while incentivising energy hubs to participate in a demand side flexibility scheme. In the first step, we formulate the optimization of the hub network and propose a novel approach to quantify the flexibility potential of the hubs. The energy hubs then provide the operator with their projected load and flexibility potential for the next day. Subsequently, the operator designs day-ahead tariffs to utilize this flexibility. The tariff incorporates the objectives of the network operator, reduction of carbon emissions in this study, while minimizing the energy costs. Finally, the energy hubs respond to the tariffs using a receding horizon controller to minimize the energy cost over the next day by exploiting building flexibility and both grids. An extensive numerical study on an network of 3 hubs with buildings of different sizes shows that the proposed pricing model can significantly reduce the carbon emissions with a low energy cost trade-off.

关键词： Costs Buildings Tariffs Carbon dioxide Pricing Numerical simulation Numerical models

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FPGA-based Real-Time High-resolution Image Processing for rocket on-board processing 17

FPGA-based Real-Time High-resolution Image Processing for ro...

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17th IEEE International Conference on computer Research and Development, ICCRD 2025

作者： Zhou, Hui Wang, Xiaofeng Xie, Yujia Cao, Yongxiang Tang, Yu Huo, Yongchun Wen, Huan Zhao, Xiongbo Li, Chaoran National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute Beijing China Beihang University Computer Science and Engineering Beijing China Beihang University National Superior College for Engineers Beijing China

ISBN: (纸本)9798331531881

The structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-Time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. This paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. This approach yields a 1.29x improvement in computing unit utilization compared to state-of-The-Art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. The overall computing efficiency, excluding the first layer, exceeded 90%. The peak computing power for the four cores reached 1638.4 GOPS, and the end-To-end computation time for

关键词： Image enhancement

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FPGA-based Real-time High-resolution Image Processing for rocket on-board processing

FPGA-based Real-time High-resolution Image Processing for ro...

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International Conference on computer Research and Development (ICCRD)

作者： Hui Zhou Xiaofeng Wang YuJia Xie Yongxiang Cao Yu Tang Yongchun Huo Huan Wen Xiongbo Zhao Chaoran Li Beijing Aerospace Automatic Control Institute National key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China Computer Science and Engineering Beihang University Beijing China National Superior College for Engineers Beihang University Beijing China

ISBN: (数字)9798331531881

ISBN: (纸本)9798331531898

The structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. This paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. This approach yields a 1.29x improvement in computing unit utilization compared to state-of-the-art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. The overall computing efficiency, excluding the first layer, exceeded 90%. The peak computing power for the four cores reached 1638.4 GOPS, and the end-to-end computation time for

关键词： YOLO Rockets Power demand Convolution Multicore processing Reviews Scalability Accelerator architectures Real-time systems Field programmable gate arrays

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Frequency Domain Auto-tuning of Structured LPV controllers for High-Precision Motion control

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory HUNREN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

关键词： Technological innovation Sensitivity Frequency-domain analysis Stability criteria Prototypes Throughput Frequency response Motion control Optimization MIMO communication

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Software-defined event-based camera and vision algorithms for digitizing highly dynamic manufacturing tasks

Software-defined event-based camera and vision algorithms fo...

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2024 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2024

作者： Walker, Emily Turner, Christopher J. Oyekan, John Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom Surrey Business School The University of Surrey Surrey GuildfordGU2 7XH United Kingdom Real Time & Distributed Systems Group Department of Computer Science University of York Heslington YorkYO10 5GH United Kingdom

ISBN: (纸本)9781837242672

Event-based cameras are inspired by the way the retina in the eye process information. Rather than capturing image frames at a constant rate, event cameras generate data asynchronously, based on changes in pixel value between frames. As a result, these cameras have a high spatiotemporal accuracy, low power constraints and reduced artefacts from motion blur. Hence, they represent favourable properties for digitizing highly dynamic manufacturing tasks such as machine vibrations and rapid human assembly actions. However, the costs of event-based cameras are prohibitively high for small to medium sized enterprises (SMEs). In this research, we present the development of a rig that combines low-cost visual sensors with low-cost algorithms to perform action recognition for highly dynamic manual manufacturing tasks. We applied our algorithms to achieve an action classification system via a novel threshold-based approach and in parallel use a neural network to perform classification of objects in the video feed. The results achieved demonstrated that our approach was able to successfully identify various rapid manual tasks being performed on identified objects. In addition to SMEs, our approach would be suited for providing low-cost digitization on legacy machines. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/).

关键词： Machine vibrations

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Behavioural Swarm Optimisation for Stable Slung-Load Aerial Transportation

Behavioural Swarm Optimisation for Stable Slung-Load Aerial ...

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Congress on Evolutionary Computation

作者： Jingyu Chen John Oyekan Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Department of Computer Science University of York York United Kingdom

Collaboration of agents in a natural swarm enables the accomplishment of tasks that would be difficult or impossible for a single agent to complete alone. For example, a swarm of autonomous Unmanned Aerial Vehicles (UAVs) enables the collaborative sensing of bulky loads for transportation over impassable terrains when the load weighs several times more than each UAV. In this work, we propose a hierarchical algorithmic architecture that supports the search and coverage of various unknown payload profiles for subsequent transportation. The grasping formation of UAVs over the payload emerges from the synthetic behaviours in the architecture without any path planning. Experiments show that our proposed design can be successfully applied in searching and coverage of various loads and has been validated in the real world through the use of Crazyflie micro-UAVs. Furthermore, the proposed grasping formation satisfies static equilibrium thereby reducing orientation changes in the load-swarm system during transportation.

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A Linear Parameter-Varying Approach to Data Predictive control

arXiv

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arXiv 2023年

作者： Verhoek, Chris Berberich, Julian Haesaert, Sofie Tóth, Roland Abbas, Hossam S. The Control Systems Group Eindhoven University of Technology Netherlands The University of Stuttgart Institute for Systems Theory and Automatic Control Germany The Institute for Electrical Engineering in Medicine Universität zu Lübeck Germany The Systems and Control Lab Institute for Computer Science and Control Hungary

By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-feedback and state-feedback-based LPV-DPC methods with terminal ingredients, which guarantee exponential stability and recursive feasibility. We provide methods for the data-based computation of these terminal ingredients. Furthermore, an in-depth analysis of the application and implementation aspects of the LPV-DPC schemes is given, including application for nonlinear systems and handling noisy data. We compare and demonstrate the performance of the proposed methods in a detailed simulation example involving a nonlinear unbalanced disc system. © 2023, CC BY-NC-SA.

关键词： Predictive control systems

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Image Segmentation Algorithm of Ischemic Stroke based on Wavelet Pooling Neural Network 2

Image Segmentation Algorithm of Ischemic Stroke based on Wav...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Zhu, Huiyuan Zhai, Yao Wu, Jinghe Lu, Chuwei Zhang, Xianchao Li, Ruide Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China College of Medicine Jiaxing University Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Department of Nursing Jiaxing China Beijing Institute of Technology School of Information and Electronics Beijing China Aviation Industry Corporation of China Avic Xi' An Flight Automatic Control Research Institute Xi'an China Jiaxing University Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Jiaxing China

ISBN: (纸本)9798331515669

Ischemic stroke is a high-risk brain disease that causes disability or death in adults worldwide. Rapid diagnosis and treatment, as well as segmentation of ischemic lesions from stroke medical images so that doctors can evaluate and develop treatment plans, are crucial to reducing brain damage. Currently, doctors' manual segmentation of lesions is time-consuming and labor-intensive and prone to missed or misdiagnosed diagnoses, delaying the best time for treatment. A well-trained neural network is considered as an effective aid for image segmentation tasks. However, in the traditional neural network down-sampling process, the pooling layer loses feature information, and the lost information significantly impacts the edge regions. While for medical images, edge regions are crucial features in the segmentation process. Therefore, to address the above issues, in this paper we improve upon the existing stroke lesion segmentation algorithm U-net, we design a segmentation network based on wavelet pooling and attention mechanisms. The network was tested on ISLES 2018 and ISLES 2022 datasets, and the Dice coefficient improved by 2.13% and 1.93% compared to baseline network, respectively. © 2024 IEEE.

关键词： Image segmentation

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Towards construction of analog solver of Schroedinger and Ginzburg-Landau equation based on Long Line

arXiv

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arXiv 2023年

作者： Pluszyński, Lukasz Pomorski, Krzystof Cracow University of Technology Department of Computer Science Poland Cracow University of Technology Department of Automatic Control and Computer Engineering Poland Quantum Hardware Systems Lodz Poland

The analog electronic computers are a type of circuitry used to calculate specific problems using the physical relationships between the voltages and currents following classical laws of physics. One specific class of these circuits are computers based on the interactions between passive circuit elements. Models presented by Gabriel Kron in 1945 are the example of using such passive elements to construct a solver for the problem of free quantum particles confined by rectangular potential. Numerical validation of Kron's second model is conducted for different shapes of particle confining potential. Kron's model is generalized by introduction of non-linear resistive elements what implies deformation of Schroedinger equation solution into Ginzburg-Landau form. © 2023, CC BY.

关键词： Analog computers

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