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robust algorithm Using Delay for Multi-Agent Systems

IFAC-PapersOnLine 2016年第13期49卷 25-30页

作者： Furtat, Igor B. Nekhoroshikh, Artem N. Tarasov, Mikhail S. Institute for Problems of Mechanical Engineering Russian Academy of Sciences 61 Bolshoy ave V.O. St.-Petersburg 199178 Russia ITMO University 49 Kronverkskiy ave Saint Petersburg197101 Russia

The paper describes the robust control algorithm for linear multi-agent systems under parametric and structural uncertainties and external unmeasured disturbances. The proposed algorithm is based on left hand side differences for estimation of the derivatives. The resulting algorithm ensures required accuracy of difference between the plant output and the reference signal. The modeling results illustrate the effectiveness of the algorithm. © 2016

关键词： Multi agent systems Delay control systems Lyapunov functions robust control Software agents Time delay Descriptors Lyapunov Krasovskii functionals Model results Plant output Reference signals robust algorithm Structural uncertainty

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robust and precise algorithm for aspheric surfaces characterization by the conic section

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JOURNAL OF THE EUROPEAN OPTICAL SOCIETY-RAPID PUBLICATIONS 2017年第1期13卷 1-7页

作者： Kren, Petr Czech Metrol Inst Okruzni 31 CZ-63800 Brno Czech Republic

Background: A new algorithm for precise characterisation of rotationally symmetric aspheric surfaces by the conic section and polynomial according to the ISO 10110 standard is described. Methods: The algorithm uses only the iterative linear least squares. It uses fitting the surface form in a combination with terms containing its spatial derivatives that represent infinitesimal transformations of form. Results: The algorithm reaches sub-nanometre residuals even though the aspheric surface is translated and rotated in the space. Conclusion: he algorithm is computationally robust and an influence of local surface imperfections can be easily reduced by use of a criterion for residuals.

关键词： Aspheric lens robust algorithm Least squares fitting Metrology ISO 10110

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robust algorithm to estimate fault synchrophasor from fault-transient synchrophasor in phasor data concentrator

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第2期9卷 124-132页

作者： Das, Sarasij Sidhu, Tarlochan Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON Canada

A fault-transient synchrophasor is computed over a window of pre-fault and fault samples. A fault synchrophasor is computed over a window of fault samples only. Fault-transient synchrophasors are discarded and are generally not used in the synchrophasor applications. Recently, an algorithm has been proposed to compute fault synchrophasor from fault-transient synchrophasor in phasor data concentrator (PDC). The accuracy of the existing algorithm deteriorates due to fault-induced transients and inaccurate fault starting time. A robust algorithm has been proposed to compute fault synchrophasor from fault-transient synchrophasor in PDC. The proposed algorithm does not use fault starting time in the calculations. It also performs better than the existing algorithm when fault-induced transients are present in the signal. The proposed algorithm is simple, non-iterative and performs satisfactorily in various investigated scenarios. The advantage of the proposed algorithm has been demonstrated in the context of fault location application.

关键词： fault location phasor measurement power system transients synchrophasor fault estimation fault-transient synchrophasor phasor data concentrator fault-induced transients PDC noniterative algorithm fault location application robust algorithm

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SHERPA: Explainable robust algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks 45

SHERPA: Explainable Robust Algorithms for Privacy-Preserved ...

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45th IEEE Symposium on Security and Privacy (SP)

作者： Sandeepa, Chamara Siniarski, Bartlomiej Wang, Shen Liyanage, Madhusanka Univ Coll Dublin Sch Comp Sci Dublin Ireland

ISBN: (纸本)9798350331318;9798350331301

With the rapid progression of communication and localisation of big data over billions of devices, distributed Machine Learning (ML) techniques are emerging to cater for the development of Artificial Intelligence (AI)-based services in a distributed manner. Federated Learning (FL) is such an innovative approach to achieve a privacy-preserved AI that facilitates ML model sharing and aggregation while keeping the participants' data at the original source. However, recent research has investigated threats from poisoning attacks in FL. Several robust algorithms based on techniques such as similarity metrics or anomaly filtering are proposed as solutions. Yet, these approaches do not focus on investigating the intentions of the attackers or providing justifications and evidence for suspecting the behaviour of clients who are considered poisoners. Therefore, we propose SHERPA, a robust algorithm that uses Shapley Additive Explanations (SHAP) to identify potential poisoners in an FL system. Based on this, we develop a novel algorithm to differentiate poisoners via feature attribution clustering. We launch data poisoning attacks for different scenarios on multiple datasets and showcase our solution to mitigate the attacks. Furthermore, we show that privacy-targeted poisoning attacks can be mitigated with our approach. Accompanying the Explainable AI (XAI) technique for defence, our study reveals the potential for post-hoc feature attributions in countering data poisoning attacks with better explainability and improved justification in eliminating potentially malicious clients in the aggregation process.

关键词： Federated Learning XAI SHAP Data Poisoning Beyond 5G/6G Privacy Defence robust algorithm

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A robust algorithm for Real-Time Peak Detection of Photoplethysmograms Using a Personal Computer Mouse

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IEEE SENSORS JOURNAL 2015年第8期15卷 4651-4659页

作者： Tran, Thang Viet Chung, Wan-Young Pukyong Natl Univ Dept Elect Engn Busan 608739 South Korea

Monitoring the photoplethysmogram (PPG) signal is essential for cardiovascular patients in the hospital or at home, as well as for those working in front of a personal computer (PC) at the office every day. Therefore, we developed a wireless PPG mouse that consists of a PC mouse, PPG sensor, and Bluetooth mote. The sensor is located within the PC mouse, therefore, the structure of the ordinary mouse is not changed. A user's thumb can easily touch the surface of a sensor for PPG signal monitoring. However, it is challenging to process the signals collected from the PPG mouse, especially in the cases where the mouse moves quickly or the user performs multiple actions on the mouse buttons. In this paper, we propose a robust algorithm to detect the PPG peak under big motion artifact conditions. In the proposed algorithm, an adaptive method enables simultaneous detection of true peaks and eliminates fake peaks from the acquired PPG signal. Next, these detected error peaks can be corrected by a random error estimator. The combination of two sequential methods enhances the robustness of the algorithm for distinguishing irregular PPG patterns. The proposed algorithm presents an advantage for real-time applications and continuous heart rate monitoring systems using a wireless PPG sensor implemented in a PC mouse.

关键词： robust algorithm photoplethysmogram (PPG) PPG mouse real-time peak detection

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robust and fast algorithm for estimating fundamental periodicity of jet engine modulation signals

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IET RADAR SONAR AND NAVIGATION 2016年第7期10卷 1286-1294页

作者： Yong, Yang Woo Hoon, Park Ji Young, Song Won Hoon, Myung Noh Hanwha Thales Radar Res Ctr Seoul South Korea Agcy Def Dev Technol Ctr POB 35-3 Yuseong Daejeon South Korea Korea Adv Inst Sci & Technol Dept Elect Engn 335 Gwahangno Daejeon 305701 South Korea

Jet engine modulation (JEM), a modulation phenomenon induced by a rotating jet engine compressor, is a representative feature extracted from the radar for aircraft target recognition. In this study, the authors present a robust and fast algorithm for extracting the spool rate, which imparts fundamental periodicity to JEM signals. First, a wavelet decomposition with Meyer wavelet was applied to the analytic form of the JEM signal. Then, the decomposition components were combined to achieve a sufficient energy and minimise the mean of the JEM auto-correlation. Finally, the peak detection algorithm was employed for automatic estimation of the spool rate. Application results of measured JEM signals demonstrated that the proposed algorithm is effective for stable and accurate extraction of the jet engine information.

关键词： object recognition radar detection wavelet transforms feature extraction correlation methods jet engines radar target recognition compressors automatic spool rate estimation peak detection algorithm JEM auto-correlation decomposition components Meyer wavelet wavelet decomposition JEM signals spool rate extraction aircraft target recognition representative feature extraction rotating jet engine compressor jet engine modulation signals fundamental periodicity estimation fast algorithm robust algorithm

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robust management in smart grids in the presence of prosumers based on PV-storage

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ENERGY REPORTS 2025年 13卷 2482-2501页

作者： Salehabadi, Kazem Moghaddam, Mahmoud Samiei Davarzani, Reza Hoseinpour, Hesamodin Islamic Azad Univ Dept Elect Engn Shahrood Branch Shahrood Iran Islamic Azad Univ Dept Elect Engn Damghan Branch Damghan Iran

This research introduces a novel application of Mixed Integer Second Order Conic Programming (MISOCP) combined with a tailored Column-and-Constraint Generation (C&CG) algorithm for the advanced management of energy and load in dynamic smart grids with prosumers. The framework addresses critical gaps in existing methods by integrating a customized multi-objective optimization approach to minimize energy losses, voltage deviations, load shedding costs, and prosumer electricity expenses. A novel aspect of the methodology is its ability to handle uncertainties in renewable generation and load demand, ensuring robust and scalable optimization across diverse grid scenarios. The proposed approach is validated through extensive simulations on the IEEE 33-node system, the IEEE 118-bus system, and a real-world Tehran distribution grid, showcasing its practicality and effectiveness. Results demonstrate significant improvements, including a 15.3 % reduction in grid losses, a 12.4 % improvement in voltage stability, and enhanced prosumer participation in energy transactions. Furthermore, the model achieves superior performance in scalability, computational efficiency, and adaptability compared to existing methods. This study contributes a comprehensive and innovative framework that enhances the sustainability and efficiency of active distribution grids, making it a valuable tool for modern smart grid applications.

关键词： Smart grid Energy storage system Renewable resources Prosumers robust algorithm

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robust load and energy management in smart grids with prosumer-integrated distributed energy resources

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JOURNAL OF CLEANER PRODUCTION 2025年 496卷

作者： Habib, Salman King Fahd Univ Petr & Minerals Dept Control & Instrumentat Engn Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Interdisciplinary Res Ctr Smart Mobil & Logist IRC SML Dhahran 31261 Saudi Arabia

This study introduces the Resilient Prosumer-Centric Energy Optimization Framework (RPEOF), a robust two- stage optimization model developed using Mixed Integer Second-Order Conic Programming (MISOCP) to address uncertainties in load demand and renewable generation within smart grids with integrated prosumers. RPEOF effectively accommodates diverse prosumer resources, including electric vehicles, batteries, and photovoltaic (PV) systems, ensuring optimal energy scheduling across entities that both produce and consume energy. By leveraging a two-stage robust optimization approach, RPEOF ensures resilience against fluctuations in renewable generation and load variations, delivering stable energy management solutions under uncertain conditions. The framework integrates the Column-and-Constraint Generation (C&CG) algorithm to enhance computational efficiency, making it suitable for large-scale and real-time applications. Simulation results highlight significant advancements, including an 18% reduction in grid energy losses, a 15.2% decrease in voltage fluctuations, a 12% increase in prosumer electricity sales, and a zero load-shedding rate, alongside a 60% reduction in computation time compared to conventional methods. Extensive testing on a 33-node test network and an actual urban grid demonstrates RPEOF's scalability and real-world applicability, emphasizing its potential to advance smart grid efficiency and support sustainable energy systems.

关键词： Smart grid Energy storage system Photovoltaic energy Prosumers robust algorithm Electric vehicle

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robust distributed adaptation under arctangent and maximum correntropy criterion

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SIGNAL IMAGE AND VIDEO PROCESSING 2024年第11期18卷 8105-8118页

作者： Wang, Shengwei Xu, Yurong Ci, Caihong Xu, Tianci Cui, Shuohao Chen, Hongquan Northwest Normal Univ Coll Comp Sci & Engn Lanzhou 730000 Peoples R China Northwest Minzu Univ Coll Med Coll Lanzhou 730000 Peoples R China Northwest Normal Univ Coll Phys & Elect Engn Lanzhou 730000 Peoples R China

In this paper, the problem of robust distributed estimation in undirected networks is explored in depth. The Arctangent framework has garnered widespread adoption for adaptive estimation in prior research, with numerous adaptive estimation algorithms stemming from this foundation. However, the integration of the Arctangent framework with the maximum correntropy criterion, and its potential for enhanced estimation results, remains unexplored. In this paper, we have conducted a study in distributed networks and proposed a new robust distributed estimation algorithm using the Arctangent framework and the maximum correntropy criterion. Simulation experiments demonstrate that the proposed algorithm exhibits superior performance compared to the benchmark algorithm in both Gaussian and impulsive noise environments. Finally, a theoretical analysis of the proposed algorithm is conducted.

关键词： Distributed Estimation robust algorithm Adaptive Filtering Maximum correntropy criterion

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ROCS: robust One-Bit Compressed Sensing With Application to Direction of Arrival

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2024年 72卷 2407-2420页

作者： Li, Xiao-Peng Shi, Zhang-Lei Huang, Lei So, Anthony Man-Cho So, Hing Cheung Shenzhen Univ State Key Lab Radio Frequency Heterogeneous Integr Shenzhen 518060 Peoples R China China Univ Petr East China Coll Sci Qingdao 266580 Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

One-bit compressed sensing (1-bit CS) inherits the merits of traditional CS and further reduces the cost and burden on the hardware device via employing the 1-bit analog-to-digital converter. When the measurements do not involve sign flips caused by additive noise, most contemporary algorithms can attain excellent signal restoration. However, their recovery performance might significantly degrade if there is even a small portion of sign flips. In order to increase the estimation accuracy in noisy scenarios, we devise a new signal model for 1-bit CS to attain robustness against sign flips. Then, we give a double-sparsity optimization formulation of the restoration problem. Subsequently, we combine proximal alternating minimization and projected gradient descent to tackle the problem. Different from existing robust methodologies, our approach, referred to as robust one-bit CS (ROCS), does not require the number of sign flips. Furthermore, we analyze the convergence behavior of ROCS and show that the objective value and variable sequences converge. Numerical results using synthetic data demonstrate that ROCS is superior to the competing methods in terms of reconstruction error in noisy environments. ROCS is also applied to direction-of-arrival estimation and outperforms state-of-the-art approaches.

关键词： Noise Quantization (signal) Noise measurement Vectors Signal processing algorithms Minimization Estimation robust algorithm one-bit compressed sensing direction-of-arrival estimation l(0)-norm optimization

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