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Bridge the Present and Future: A Cross-Layer Matching Game in Dynamic Cloud-Aided Mobile Edge Networks

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arXiv 2023年

作者： Qi, Houyi Liwang, Minghui Wang, Xianbin Li, Li Gong, Wei Jin, Jian Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China The Department of Electrical and Computer Engineering Western University ON Canada The Department of Control Science and Engineering Tongji University Shanghai China The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The Research Institute of Industrial Internet of Things CAICT China The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

Cloud-aided mobile edge networks (CAMENs) allow edge servers (ESs) to purchase resources from remote cloud servers (CSs), while overcoming resource shortage when handling computation-intensive tasks of mobile users (MUs). Conventional trading mechanisms (e.g., onsite trading) confront many challenges, including decision-making overhead (e.g., latency) and potential trading failures. This paper investigates a series of cross-layer matching mechanisms to achieve stable and cost-effective resource provisioning across different layers (i.e., MUs, ESs, CSs), seamlessly integrated into a novel hybrid paradigm that incorporates futures and spot trading. In futures trading, we explore an overbooking-driven aforehand cross-layer matching (OA-CLM) mechanism, facilitating two future contract types: contract between MUs and ESs, and contract between ESs and CSs, while assessing potential risks under historical statistical analysis. In spot trading, we design two backup plans respond to current network/market conditions: determination on contractual MUs that should switch to local processing from edge/cloud services;and an onsite cross-layer matching (OS-CLM) mechanism that engages participants in real-time practical transactions. We next show that our matching mechanisms theoretically satisfy stability, individual rationality, competitive equilibrium, and weak Pareto optimality. Comprehensive simulations in real-world and numerical network settings confirm the corresponding efficacy, while revealing remarkable improvements in time/energy efficiency and social welfare. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

Semantic-Consistent Deep Quantization for Cross-modal Retrieval 11

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Semantic-Consistent Deep Quantization for Cross-modal Retrie...

11th International Conference on Intelligent control and Information Processing, ICICIP 2021

作者： Ma, Liya Zhang, Nian Shu, Kuang I. Zou, Xitao Southwest University College of Computer and Information Science Chongqing400715 China University of the District of Columbia Department of Electrical and Computer Engineering WashingtonDC20008 United States Liuzhou Yunde Electronic Technology Co. Ltd Research and Develop Center Guangxi Autonomous Region Liuzhou545005 China

ISBN: (纸本)9781665425155

With making up for the deficiency of the constraint representation capability of hashing codes for high-dimensional data, the quantization method has been found to generally perform better in cross-modal similarity retrieval research. However, in current quantization approaches, the codebook, as the most critical basis for quantization, is still in a passive status and detached from the learning framework. To improve the initiative of codebook, we propose a semantic-consistent deep quantization (SCDQ), which is the first scheme to integrate quantization into deep network learning in an end-to-end fashion. Specifically, two classifiers following the deep representation learning networks are formulated to produce the class-wise abstract patterns with the help of label alignment. Meanwhile, our approach learns a collaborative codebook for both modalities, which embeds bimodality semantic consistent information in codewords and bridges the relationship between the patterns in classifiers and codewords in codebook. By designing a novel algorithm architecture and codebook update strategy, SCDQ enables effective and efficient cross-modal retrieval in an asymmetric way. Extensive experiments on two benchmark datasets demonstrate that SCDQ yields optimal cross-modal retrieval performance and outperforms several state of-the-art cross-modal retrieval methods. © 2021 IEEE.

关键词： Deep neural networks

Distributed formation control of networked mechanical systems

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arXiv 2022年

作者： Javanmardi, Najmeh Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach. © 2022, CC BY.

关键词： Networked control systems

Robust Voltage control in DC Networks with Uncertain Nonlinear Load Dynamics

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Robust Voltage Control in DC Networks with Uncertain Nonline...

IEEE Conference on Decision and control

作者： Amirreza Silani Giacomo Casadei Michele Cucuzzella Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen AG Groningen The Netherlands Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Laboratoire Ampere Dpt. EEA of the Ecole Centrale de Lyon Université de Lyon Ecully France Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this letter, we propose a control scheme for regulating the voltage in Direct Current (DC) power networks. In contrast with other works in the literature where the loads are assumed to be constant, we consider uncertain time-varying loads described as the outputs of nonlinear dynamical exosystems with uncertain parameters. Based on the output regulation methodology, the proposed control scheme ensures the robust stability of the overall network and achieves voltage regulation in presence of impedance (Z), current (I), and power (P) loads. The simulation results illustrate excellent performance of the proposed control scheme.

关键词： Robust stability Simulation Regulation Impedance Voltage control

Minimum structural sensor placement for switched linear time-invariant systems and unknown inputs

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arXiv 2021年

作者： Reed, Emily A. Ramos, Guilherme Bogdan, Paul Pequito, Sérgio Ming Hsieh Electrical and Computer Engineering Department University of Southern California United States Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal University of Southern California Ming Hsieh Electrical and Computer Engineering Department Delft University of Technology Delft Center for Systems and Control

In this paper, we study the structural state and input observability of continuous-time switched linear time- invariant systems and unknown inputs. First, we provide necessary and sufficient conditions for their structural state and input observability that can be efficiently verified in O((m(n + p))2), where n is the number of state variables, p is the number of unknown inputs, and m is the number of modes. Moreover, we address the minimum sensor placement problem for these systems by adopting a feed-forward analysis and by providing an algorithm with a computational complexity of O((m(n + p) + α)2.373), where α is the number of target strongly connected components of the system's digraph representation. Lastly, we explore different assumptions on both the system and unknown inputs (latent space) dynamics that add more structure to the problem, and thereby, enable us to render algorithms with lower computational complexity, which are suitable for implementation in large-scale systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Time varying control systems

Fault-tolerant quantum computation using large spin cat-codes

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arXiv 2024年

作者： Omanakuttan, Sivaprasad Buchemmavari, Vikas Gross, Jonathan A. Deutsch, Ivan H. Marvian, Milad Center for Quantum Information and Control University of New Mexico AlbuquerqueNM United States Department of Physics and Astronomy University of New Mexico AlbuquerqueNM United States Google Quantum AI VeniceCA90291 United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States

We construct a fault-tolerant quantum error-correcting protocol based on a qubit encoded in a large spin qudit using a spin-cat code, analogous to the continuous variable cat encoding. With this, we can correct the dominant error sources, namely processes that can be expressed as error operators that are linear or quadratic in the components of angular momentum. Such codes tailored to dominant error sources can exhibit superior thresholds and lower resource overheads when compared to those designed for unstructured noise models. A key component is the CNOT gate that preserves the rank of spherical tensor operators. Categorizing the dominant errors as phase and amplitude errors, we demonstrate how phase errors, analogous to phase-flip errors for qubits, can be effectively corrected. Furthermore, we propose a measurement-free error correction scheme to address amplitude errors without relying on syndrome measurements. Through an in-depth analysis of logical CNOT gate errors, we establish that the fault-tolerant threshold for error correction in the spin-cat encoding surpasses that of standard qubit-based encodings. We consider a specific implementation based on neutral-atom quantum computing, with qudits encoded in the nuclear spin of 87Sr, and show how to generate the universal gate set, including the rank-preserving CNOT gate, using quantum control and the Rydberg blockade. These findings pave the way for encoding a qubit in a large spin with the potential to achieve fault tolerance, high threshold, and reduced resource overhead in quantum information processing. © 2024, CC0.

关键词： Qubits

A scalable distributed dynamical systems approach to compute the strongly connected components and diameter of networks

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arXiv 2021年

作者： Reed, Emily A. Ramos, Guilherme Bogdan, Paul Pequito, Sérgio Ming Hsieh Electrical and Computer Engineering Department University of Southern California United States Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal Delft University of Technology Delft Center for Systems and Control

Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of discrete optimization problems, and subsequently, machine learning and control theory problems. On the one hand, SCCs are used in solving the 2-satisfiability problem, which has applications in clustering, scheduling, and visualization. On the other hand, the diameter has applications in network learning and discovery problems enabling efficient internet routing and searches, as well as identifying faults in the power grid. In this paper, we leverage consensus-based principles to find the SCCs in a scalable and distributed fashion with a computational complexity of O (Ddmax in-degree ) , where D is the (finite) diameter of the network and dmax in-degree is the maximum in-degree of the network. Additionally, we prove that our algorithm terminates in D + 1 iterations, which allows us to retrieve the diameter of the network. We illustrate the performance of our algorithm on several random networks, including Erdos-Rényi, Barabási- Albert, and Watts-Strogatz networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Optimization

Super Twisting Sliding Mode control Strategy for a Three-Level T-Type Dual MPPT Inverter

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Super Twisting Sliding Mode Control Strategy for a Three-Lev...

Compatibility in Power Electronics (CPE)

作者： Farzaneh Bagheri Naki Guler Marco Rivera Hasan Komurcugil Department of Electrical and Electronic Engineering Antalya Bilim University Antalya Turkey Electrical and Electronic Engineering Technology Faculty Gazi University Ankara Turkey Renewable Energy and Smart Grids Application and Research Center Gazi University Ankara Turkey Power Electronics Machines and Control (PEMC) Research Institute University of Nottingham Nottingham UK Laboratorio de Conversión de Energías y Electrónica de Potencia (LCEEP) Vicerrectoría Académica Universidad de Talca Curicó Chile Department of Computer Engineering Eastern Mediterranean University (EMU) Famagusta Turkey

ISBN: (数字)9798331515171

ISBN: (纸本)9798331515188

Nowadays Residential and small commercial power systems are taking advantage of the dual maximum power point tracking (MPPT) inverters, optimizing energy harvesting from two individual solar panel arrays to increase performance and energy output. Three-level T-type inverters are also famous due to their lower total harmonic distortion, high efficacy, and lower voltage stress on the switch which are a good option to be integrated into the dual MPPT solar plants. So, this article incorporates the dual MPPT solar plants with a T-Type grid-connected inverter which uses a double super twisting sliding mode control (STSMC) to control the injected currents to the grid in d and q reference frames. The STSMC mitigates chattering while showing robustness under model variations and dynamic response. The efficiency of the proposed control method under different irradiation values is verified through simulation results.

关键词： Maximum power point trackers Total harmonic distortion Switches Inverters Robustness Real-time systems Solar panels Time factors Voltage control Sliding mode control

Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality