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2024 International Conference on Information and Communication Technology for Development for Africa, ICT4DA 2024

作者： Hailu, Gashaye L. Yetayew, Tefera T. Bahir Dar University Electrical and Computer Engineering Faculty Bahir Dar Institute of Technology Bahir Dar Ethiopia Adama Science and Technology University Department of Power and Control Engineering Adama Ethiopia

ISBN: (纸本)9798331527792

In this research, nature inspired metaheuristic optimization algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Techniques are formulated to tune optimal combinations of PID controller parameters for a quadruple tank level control application. The degree of relation of the best paring for both interacted control loops are justified by using Relative Gain Array (RGA) calculation. The overall system has been modeled and implemented in MATLAB/Simulink and performance evaluations has been done for time domain performance specifications of settling time, rise time, percentage overshoot and steady state error as comparison criterions of controllers. Accordingly, for the minimum phase case, GA tuned PID has settling time of 0.36sec and 0.31second for the tank 1 and tank 2 respectively. And PSO tuned PID controller has settling time of 0.96sec and 0.35sec for tank 1and tank 2 respectively. The quantitative and qualitative analysis of results reveals that there is fast dynamic response using GA PID relative to PSO PID even though the difference is not significant that may be due to stochastic feature of the metahueristic optimization algorithms. In summary, the optimal combination of PID controller algorithms' parameters can give robust performance compared to PID controller designed using the classical approaches or manual tuning techniques. © 2024 IEEE.

关键词： Genetic algorithms

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Intelligent Execution of computer Vision Tasks in Delay-Constrained UAV-Aided Networks

Intelligent Execution of Computer Vision Tasks in Delay-Cons...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Varshney, Nancy Puligheddu, Corrado Chiasserini, Carla Fabiana Casetti, Claudio De, Swades Indian Institute of Technology Department of Electrical Engineering Delhi India Department of Electronics and Telecommunications Politecnico di Torino Italy Department of Control and Computer Engineering Politecnico di Torino Italy

ISBN: (纸本)9798350370218

Autonomous unmanned aerial vehicles (UAVs) are crucial in critical target tracking and disaster management services. However, challenges arise due to limited channel capacity causing large transmission delays and constraints imposed by UAV batteries when running computationally intensive object detection and tracking algorithms. To address this, we propose in-telligent offloading computer vision tasks to a high-computational edge server at millimeter wave (mmWave) frequency. Transmission at mmWave needs large transmission power and is susceptible to blockages that necessitate considering the link quality in the offloading policy. Additionally, the timely processing of frames containing objects of interest is essential for context-based UAV operations to achieve a low frame drop rate. In this work, we present a delayed-reward reinforcement learning framework to determine the offloading policy of computer vision tasks in a delay-constrained environment. This approach considers the importance of the content within frames, which is unknown to the UAV. The objective is to jointly reduce UAV energy consumption and frame drop rates, leveraging statistical information of both the channel and the frame semantics. Through extensive simulations, we demonstrate by considering statistical information of the communication channel and frame semantics, we achieve approximately 45% energy savings compared to the UAV's energy consumption when processing all frames locally and maintaining the drop rate of delay-constrained frames below 5%. © 2023 IEEE.

关键词： Communication channel delay frame semantics offloading unmanned aerial vehicle (UAV)

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Fault-Tolerant Quantum Computation Using Large Spin-Cat Codes

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PRX Quantum 2024年第2期5卷 020355-020355页

作者： Sivaprasad Omanakuttan Vikas Buchemmavari Jonathan A. Gross Ivan H. Deutsch Milad Marvian Center for Quantum Information and Control Department of Physics and Astronomy Venice California 90291 USA Department of Electrical and Computer Engineering

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.

关键词： Quantum computation Quantum control Quantum error correction Quantum information theory

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On Mikhailov Stability Conditions for a Class of Integer-and Commensurate Fractional-Order Discrete-Time Systems 21st

On Mikhailov Stability Conditions for a Class of Integer-and...

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21st Polish control Conference, PCC 2023

作者： Stanislawski, Rafal Rydel, Marek Department of Electrical Control and Computer Engineering Opole University of Technology ul. Pŕoszkowska 76 Opole45-758 Poland

ISBN: (纸本)9783031351693

The Mikhailov stability condition is a classical stability test for continuous-time systems, similar to the well-known Nyquist method. However, in contrast to the Nyquist criterion, the Mikhailov stability tests do not reach considerable research attention. This paper introduces an extension of Mikhailov stability condition for two classes of a discretetime system in terms of linear time-invariant system, and fractional-order one based on ‘forward-shifted’ Gr¨unwald-Letnikov difference. Simulation experiments confirm the usefulness of the Mikhailov methods for stability analysis of discrete-time systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Continuous time systems

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High-performance and Multi-functional control of Transformerless Single-phase Smart Inverter for Grid-connected PV System

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1386-1394页

作者： Kamran Zeb Saif Ul Islam Waqar Uddin Imran Khan Muhammad Ishfaq Tiago Davi Curi Busarello H.J.Kim Department of Electrical Engineering Pusan National University School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Control Automation and Computing EngineeringFederal University of Santa Catarina Blumenau

Highly reliable and flexible control is required for distributed generation(DG) to efficiently connect to the *** inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter(SPV-SSI) of 5 k VA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling(PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator(STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i. e., fuzzy proportional-integral(F-PI) controller and fuzzy-sliding mode controller(F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop(islanded mode) and current control loop(grid-connected mode).

关键词： Distributed generation(DG) inverter convert-er fuzzy-sliding mode controller(F-SMC) fuzzy proportionalintegral(F-PI)controller

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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Research on the Flux-weakening Capability of the Reverse-salient Permanent Magnet Synchronous Motor 26

Research on the Flux-weakening Capability of the Reverse-sal...

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26th International Conference on electrical Machines and Systems, ICEMS 2023

作者： Zhao, Xiaokun Zhang, Cheng Wang, Weinan Kou, Baoquan Zhu, Liangkuan Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Institute of Technology Department of Electrical and Automation Harbin China

ISBN: (纸本)9798350317589

Permanent magnet synchronous motors (PMSMs) offer the benefits of high torque density and a superior power factor. Nevertheless, the challenge lies in the inherent difficulty of adjusting the permanent magnet flux. To address this issue, this paper analyzes the influence of electromagnetic parameters on the constant-power speed range (CPSR). First, the analysis focuses on the influence of d-axis inductance and saliency ratio, aiming to establish a design method for achieving a wide CPSP in PMSMs. Second, based on the electromagnetic parameter requirements, a reverse-salient PMSM is proposed and its working principle is explained. Finally, the electromagnetic characteristics, including torque and the CPSP, are determined through the application of the finite element method (FEM). The obtained results confirm that the reverse-salient PMSM achieves a CPSP of 7:1, thus validating the accuracy of the theoretical analysis. © 2023 IEEE.

关键词： Finite element method

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Integrating OpenTitan as a Security controller for Cryptographic Tasks in RISC-V SoCs

Integrating OpenTitan as a Security Controller for Cryptogra...

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2025 Joint National Conference on Cybersecurity, ITASEC and SERICS 2025

作者： Musa, Alberto Parisi, Emanuele Barbierato, Luca Patti, Edoardo Acquaviva, Andrea Barchi, Francesco Università di Bologna Department of Electrical Electronic and Information Engineering "Guglielmo Marconi" Bologna Italy Politecnico di Torino Department of Control and Computer Engineering Turin Italy

RISC-V architectures are increasingly utilized in security-critical embedded systems, with OpenTitan standing out as a prominent open-source silicon Root-of-Trust. OpenTitan delivers essential functionalities, such as secure boot and execution integrity, but introduces notable area overhead. To mitigate this issue, we propose TitanSSL, a secure software stack that offloads cryptographic operations to OpenTitan. TitanSSL comprises an OpenSSL backend, a Linux driver for system communication, and a custom OpenTitan firmware. Communication between components is facilitated through a custom Application Binary Interface (ABI), ensuring the driver remains independent of the specific cryptographic operations executed by the OpenSSL engine. This design supports extensibility, enabling the integration of additional cryptographic primitives and enhancing the system flexibility. We evaluated TitanSSL on a System-on-Chip (SoC) featuring a CVA6 application core running Linux and OpenTitan, both clocked at 40 MHz on a Xilinx VCU118 FPGA. Our results reveal that, while there is communication overhead between system components, it is outweighed by substantial performance gains. Specifically, TitanSSL achieves speedups of 40x for SHA-256 and 82x for AES-256-CBC compared to a software-only implementation running on the CVA6 core. In addition, we provide design guidelines for future optimizations to improve system performance. © 2025 Copyright for this paper by its authors.

关键词： Firmware

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Fractional-order binary bat algorithm for feature selection on high-dimensional microarray data

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7453-7467页

作者： Esfandiari, Ahmad Farivar, Faezeh Khaloozadeh, Hamid Department of Computer and Mechatronics Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Systems and Control Faculty of Electrical Engineering K. N. Toosi University of Technology Seyed-Khandan Shariati Ave. Tehran16317-14191 Iran

High-dimensional microarray data suffer from the confounding effects of irrelevant, redundant and noisy genes on the scalability and efficiency of classification algorithms. In order for an effective dimensionality reduction and the selection of informative genes, this paper introduces a novel approach using fractional calculus concepts. This study proposes a modified version of binary the bat algorithm named fractional-order binary bat algorithm (FBBA) able to control the convergence process using more historical memory of bat behaviors. The gene selection technique contains a two-stage hybrid filter/wrapper method which employs a new correlation-based feature clustering (CFC) algorithm in the filter stage and the FBBA in the wrapper stage. The CFC-FBBA is evaluated on ten microarray gene expression datasets by employing the support vector machine classifier with a k-fold Monte Carlo cross validation data partitioning model. Furthermore, the results show that the CFC-FBBA, while minimizing the size of the gene subset, achieves the highest classification accuracy in most cases compared to several state-of-art hybrid techniques. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Classification (of information)

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Applying t-Distributed Stochastic Neighbor Embedding for Improving Fingerprinting-Based Localization System

IEEE Sensors Letters

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IEEE Sensors Letters 2023年第9期7卷 1页

作者： Tarekegn, Getaneh Berie Tai, Li-Chia Lin, Hsin-Piao Tesfaw, Belayneh Abebe Juang, Rong-Terng Hsu, Huan-Chia Huang, Kai-Lun Singh, Kanishk National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu30010 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei10608 Taiwan National Taipei University of Technology Department of Electrical Engineering and Computer Science Taipei10608 Taiwan Feng Chia University Department of Electronic Engineering Taichung40724 Taiwan Industrial Technology Research Institute Information and Communications Research Laboratories Hsinchu310401 Taiwan

Large-scale location estimation is crucial for many artificial intelligence Internet of Things (IoT) applications in the era of smart cities. This letter proposes a deep learning-based outdoor positioning scheme for large-scale wireless settings using fingerprinting techniques. We first developed a feature extraction technique using t-distributed stochastic neighbor embedding (t-SNE) to extract dominant and distinguishable features while eliminating noises from the radio fingerprints. Afterward, we developed a deep learning-based coarse-fine localization framework to improve positioning performance significantly. Based on our numerical analysis, the proposed scheme reduces computation time by 64.41%, and the average positioning error is 38 cm. Therefore, the proposed approach significantly improved positioning accuracy and reduced computation time. © 2017 IEEE.

关键词： Feature extraction

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