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arXiv 2025年

作者： Singhal, Shobhit Fochesato, Marta Aolaritei, Liviu Dörfler, Florian Automatic Control Laboratory ETH Zürich Switzerland Department of Electrical Engineering and Computer Sciences UC Berkeley United States

Wind power producers (WPPs) participating in short-term power markets face significant imbalance costs due to their non-dispatchable and variable production. While some WPPs have a large enough market share to influence prices with their bidding decisions, existing optimal bidding methods rarely account for this aspect. Price-maker approaches typically model bidding as a bilevel optimization problem, but these methods require complex market models, estimating other participants’ actions, and are computationally demanding. To address these challenges, we propose an online learning algorithm that leverages contextual information to optimize WPP bids in the price-maker setting. We formulate the strategic bidding problem as a contextual multi-armed bandit, ensuring provable regret minimization. The algorithm’s performance is evaluated against various benchmark strategies using a numerical simulation of the German day-ahead and real-time markets. Copyright © 2025, The Authors. All rights reserved.

关键词： Wind power

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Towards backward compatibility of ADRC: revisiting classical state-feedback control with integral compensator

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Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第2期73卷

作者： Mrotek, Mikolaj Michalski, Jacek Madonski, Rafal Pazderski, Dariusz Retinger, Marek Faculty of Control Robotics and Electrical Engineering Institute of Robotics and Machine Intelligence Poznan University of Technology Piotrowo 3a Poznan60-965 Poland Faculty of Automatic Control Electronics and Computer Science Department of Automatic Control and Robotics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznan University of Technology Piotrowo 3a Poznan60-965 Poland

In this paper, the problem of backward compatibility of active disturbance rejection control (ADRC) is investigated. The goal is to contextualize ADRC to deliver its interpretations from the established field of linear control systems. For this study, a control algorithm, denoted here as integral disturbance rejection control (IDRC), is considered that combines classical state-feedback control with an integral compensator. At first, an interpretation of ADRC is involved in terms of existing state-space control approaches. Next, a transition to the frequency domain is performed, which is justified as a significant part of practical control engineering is conducted in that domain. For assumed specific plant structures, both ADRC and IDRC are then holistically compared in terms of transfer function representation and frequency characteristics, as well as steady-state convergence conditions. Such a juxtaposition helps to highlight the similarities and differences of both approaches, whereas the utilized bandwidth parameterization is shown to bring the control system to the same form, thus indicating some interesting practical aspects. Finally, the theoretical results concerning both considered control structures are validated in a set of numerical simulations and experiments conducted on a laboratory hardware testbed. © 2025 The Author(s).

关键词： Disturbance rejection

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Analysis of Texture Synthesis Algorithms in computer Graphics

Analysis of Texture Synthesis Algorithms in Computer Graphic...

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2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2022

作者： Gurenko, Vladimir V. Eliseev, Vyacheslav A. Usmanov, Maxim O. Selezneva, Maria S. Bauman Moscow State Technical University Department of Computer Systems and Networks Moscow Russia Bauman Moscow State Technical University Department of Automatic Control Systems Moscow Russia

ISBN: (纸本)9781665409933

The use of computer graphics methods is associated with the ongoing problem of texture synthesis. There are two groups of approaches to this problem. The first one is the creating textures by a digital artist using such software tools as Substance Painter. The second group includes automatic methods based on specialized algorithms. Some examples include synthesis using non-parametric sampling, as well as machine learning algorithms based on PSGAN. This paper provides a comparative analysis based on quality and performance criteria of texture synthesis algorithms. It is worth to mention that the difficulty of assessing the quality of synthesis is caused by the lack of a formal quantitative metric. The authors made conclusions about the preferred fields for application of the analyzed algorithms. The results of this survey can be used to optimize the production activities of digital art studios in terms of the time it takes to make textures. © 2022 IEEE.

关键词： computer graphics

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The Fast Walsh-Paley Transform in The Signal Simulation Algorithm

The Fast Walsh-Paley Transform in The Signal Simulation Algo...

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2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2022

作者： Gurenko, Vladimir V. Bychkov, Boris I. Zhiglov, Georgy D. Selezneva, Maria S. Bauman Moscow State Technical University Department of Computer Systems and Networks Moscow Russia Bauman Moscow State Technical University Department of Automatic Control Systems Moscow Russia

ISBN: (纸本)9781665409933

The article considers the fast version of the random signal simulation algorithm, applicable for hardware-in-the-loop simulation of real-time systems. The simulation is performed in the spectral region of the Walsh-Paley system for specified spectral density functions. The mathematical basis of the fast algorithm is the inverse fast Walsh transform. Calculation of signal samples from the random Walsh-Paley spectrum is shown analytically and graphically. An experimental study of the algorithm was carried out on different numbers of signal samples. It's concluded that the fast version is better than the main simulation algorithm in terms of the signal recovery time. According to the experimental results, while the number of samples increases, not only does the simulation accuracy increase, but the advantage of the fast algorithm in terms of signal recovery time also grows. © 2022 IEEE.

关键词： Digital signal processing

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A DRL-Based Cluster Scheduling Algorithm Configuration Optimization Approach for Artificial Intelligence Jobs

A DRL-Based Cluster Scheduling Algorithm Configuration Optim...

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IEEE International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Shilin Wen Wei Liang Siyan Zhu Ke Qiu Xiaoning Wu Department Three of Command and Control North Automatic Control Technology Institute Taiyuan China School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040

With the widespread application of machine learning technology across multiple domains, artificial intelligence (AI) jobs have become significant workloads for cloud service providers. However, current cloud platforms rely on pre-set scheduling algorithms, making it difficult to adjust configurations in real-time according to characteristics of AI jobs, thereby limiting job completion efficiency. Additionally, the heterogeneity and dynamism of AI jobs increase the difficulty of resource prediction and scheduling. In order to address this issue, this paper proposes an effective approach based on Deep Reinforcement Learning (DRL), by using DRL technology to adjust scheduling algorithm configurations online, converting the optimization process into a Markov process for model training, so as to optimize configurations in real-time and reduce job completion time. Simultaneously, to shorten the data sampling time for DRL training, this paper develops a cluster simulation scheduler that can efficiently simulate cluster running states, which can accelerate DRL training. Experimental results demonstrate that the simulation scheduler exhibits fast simulation rates and high simulation accuracy, and our proposed approach effectively reduces job completion time in small-scale clusters, thereby enhancing cluster resource utilization.

关键词： Training Electrical engineering Limiting Scheduling algorithms Clustering algorithms Markov processes Real-time systems Resource management Artificial intelligence Optimization

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Trusted Execution of Periodic Tasks for Embedded Systems*

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IFAC-PapersOnLine 2023年第2期56卷 8845-8850页

作者： Martin Gunnarsson Nils Vreman Martina Maggio RISE Cybersecurity RISE Research Institutes of Sweden Sweden Department of Automatic Control Lund University Sweden Department of Computer Science Saarland University Germany

Systems that interact with the environment around them generally run some periodic tasks. This class of systems include, among others, embedded control systems. Embedded controllers have been proven vulnerable to various security attacks, including attacks that alter sensor and actuator data and attacks that disrupt the calculation of the control signals. In this paper, we propose, and implement, a mechanism to execute a periodic task and its communication interfaces in a trusted execution environment. This allows us to execute an isolated controller, thus offering higher security guarantees. We analyse the overhead of switching between the regular (possibly compromised) execution environment and the trusted execution environment and quantify the effect of this defence mechanism on the control performance.

关键词： Security Embedded computer architectures Embedded computer control systems and applications

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Follow me droney! Will UWB technology do it right? 12

Follow me droney! Will UWB technology do it right?

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12th Asia Conference on Mechanical and Aerospace Engineering, ACMAE 2021

作者： Hanzel, Krzysztof Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

Object tracking for consumer drones is currently a rapidly developing technology. Its implementation is currently carried out with the use of object-in-image detection, which often limits the latest possibilities of this technology. The disadvantage of such a solution is also the increase in energy demand and the need to provide additional computing power, or delays resulting from the transfer of this operation to the control device. The proposed solution to this problem in this article is the use of UWB (Ultra-wideband) technology, which is increasingly appearing in consumer devices. The possible yield related to the accuracy of determining the position of the object as well as the experimentally determined frequency of receiving information about the position was presented. Additional advantages, such as resistance to NLOS (non-line of sight) conditions, were also presented. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Quality Assessment of Electrocardiogram Signals Using Contrastive Learning 13

Quality Assessment of Electrocardiogram Signals Using Contra...

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13th International Conference on Information Technology in Medicine and Education, ITME 2023

作者： Zhong, Meiping Li, Zuoyong Wang, ChuanSheng Huang, Jiayan Zhao, WanQi Fan, Haoyi College of Computer and Big Data Fuzhou University Fuzhou350108 China College of Computer and Control Engineering Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China Polytechnic University of Catalonia Department of Automatic Control Technical Barcelona08034 Spain New Engineering Industry College Putian University Putian351100 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China

ISBN: (纸本)9798350319156

Quality assessment of electrocardiogram (ECG) signals holds significant importance in reducing the high-frequency false alarms in automated arrhythmia diagnosis. Existing quality assessment methods primarily rely on empirical threshold setting or the calculation of relevant statistical values to formulate decision rules. However, the thresholds set in this manner are typically based on experience and knowledge, resulting in decision rules that lack flexibility and struggle to adapt to changes in the dataset. To address this issue, many researchers have turned to deep learning algorithms for ECG signal quality assessment. Nevertheless, most existing deep learning methods usually require large-scale and labeled ECG data for training, whose acquiring is typically challenging. Therefore, this paper proposes an efficient method for ECG signal quality assessment. First, we use a contrast learning framework to construct sample pairs through multilevel data augmentation. Second, a densely connected convolutional network (DenseNet) is used to improve the model's ability of extracting local features in ECG signals, and a Squeeze-and-Excitation attention module is introduced to make the model pay more attention to critical features. Finally, the feature representation is learned by minimizing the contextual contrast loss to bring similar samples closer and push dissimilar samples farther away. In this way, we can utilize the contrastive learning framework to extract temporal representations from unlabeled data and transfer them to downstream ECG signal quality assessment tasks. Extensive experiments on the Physionet/CinC Challenge 2011 dataset demonstrate that our approach outperforms most existing quality assessment methods. © 2023 IEEE.

关键词： Electrocardiograms

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Adaptive Stochastic Predictive control from Noisy Data: A Sampling-based Approach

Adaptive Stochastic Predictive Control from Noisy Data: A Sa...

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IEEE Conference on Decision and control

作者： Johannes Teutsch Christopher Narr Sebastian Kerz Dirk Wollherr Marion Leibold Department of Computer Engineering Chair of Automatic Control Engineering (LSR) Technical University of Munich Theresienstr. 90 Munich Germany

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this work, an adaptive predictive control scheme for linear systems with unknown parameters and bounded additive disturbances is proposed. In contrast to related adaptive control approaches that robustly consider the parametric uncertainty, the proposed method handles all uncertainties stochastically by employing an online adaptive sampling-based approximation of chance constraints. The approach requires initial data in the form of a short input-output trajectory and distributional knowledge of the disturbances. This prior knowledge is used to construct an initial set of dataconsistent system parameters and a distribution that allows for sample generation. As new data stream in online, the set of consistent system parameters is adapted by exploiting set membership identification. Consequently, chance constraints are deterministically approximated using a probabilistic scaling approach by sampling from the set of system parameters. In combination with a robust constraint on the first predicted step, recursive feasibility of the proposed predictive controller and closed-loop constraint satisfaction are guaranteed. A numerical example demonstrates the efficacy of the proposed method.

关键词： Robust control Linear systems Uncertainty Shape Probabilistic logic Trajectory Noise measurement Synthetic aperture sonar Predictive control Convergence

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