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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wu, Dongjun Yi, Bowen Manchester, Ian R. Lund University Department of Automatic Control Box 118 LundSE-221 00 Sweden Polytechnique Montreal Department of Electrical Engineering & Gerad QCH3T 1J4 Canada The University of Sydney Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering Australia

ISBN: (纸本)9798350316339

In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on submanifolds. We demonstrate that the search for CCM on submanifolds can be reformulated as convex conditions. In particular, since Lie groups can be viewed as submanifolds in Euclidean space, the results are directly applicable to this setting. © 2024 IEEE.

关键词： Nonlinear simulations

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A Novel Architecture - Switching Echo State Networks

A Novel Architecture - Switching Echo State Networks

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IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Codrin A. Lupascu Daniel Coca Octavian C. Pastravanu Department of Automatic Control and Applied Informatics Technical University “Gheorghe Asachi” Iasi Romania School of Engineering Newcastle University Newcastle UK

ISBN: (数字)9798350361933

ISBN: (纸本)9798350361940

This paper presents a novel approach to Echo State Networks (ESNs) by integrating state-feedback with switching systems theory and the computational efficiency of Reservoir Computing architectures. We introduce an innovative architecture for ESNs, featuring a switching input weight and state-feedback gain, applicable to both linear and non-linear reservoirs. The stability of this architecture is rigorously analysed using the standard Lyapunov function construction method. Additionally, we explore the dynamical properties of a state-feedback ESN architecture used in the literature. The advantages of the proposed switching ESN is demonstrated using electrophysiological recordings in fruitfly photoreceptors.

关键词： Symmetric matrices Computer architecture Switches Voltage Reservoirs Photoreceptors Stability analysis

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RTLAB-Based Performance Validation of PV- Powered Single-Phase Asynchronous Motor Pumps 3

RTLAB-Based Performance Validation of PV- Powered Single-Pha...

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3rd International Conference on Advanced electrical engineering, ICAEE 2024

作者： Fezazi, Omar Semmak, Abdelkader Köten, Hasan El Djalil Djehaf, Mohammed Abd El Islam, Ayad Ahmed Nour Mallik, Biswadip Basu Sidi Bel-Abbes Algeria Djillali Liabes University Faculty of Electrical Engineering Department of Automatic Control Sidi Bel-Abbes Algeria Istanbul Medeniyet University Engineering Faculty Mechanical Engineering Department North Campus Uskudar Istanbul34700 Turkey Kasdi merbah university Ouargla Algeria Institute of Engineering & Management University of Engineering & Management Department of Basic Science and Humanities West Bengal Kolkata India

ISBN: (纸本)9798350349351

In this paper, a comprehensive investigation of the performance evaluation and validation of a single-phase asynchronous motor pump system coupled with a photovoltaic (PV) power source is presented. The purpose of this study was to evaluate the practicality and effectiveness of this configuration for pumping applications. The RTLAB platform, which enables real-time simulation and emulation of dynamic systems, includes important components, such as the use of a single-phase asynchronous motor as the pump's power source, the incorporation of a PV system to supply renewable energy, and the use of RTLAB for real-time validation. Through rigorous simulation and experimentation, the motor response performance, such as speed, torque, and current response, was analyzed under varying solar irradiance and load conditions. In addition, the PV power and DC bus voltage were supervised after motor driving. This research fills the knowledge gap between the theoretical analysis and real-world applications of single-phase asynchronous motor pump systems combined with PV sources. This approach, which validates the results using RTLAB, provides a validation method to evaluate the performance and guide design choices for effective and environmentally friendly pumping solutions. Keywords- Single-phase asynchronous motors, PV, RTLAB validation, SimPower System MATLAB. © 2024 IEEE.

关键词： MATLAB

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Deep Reinforcement Learning Method for control of Mixed Autonomy Traffic Systems

Deep Reinforcement Learning Method for Control of Mixed Auto...

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International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Xingyu Liu Esa Apriaskar Lyudmila Mihaylova Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Electrical Engineering Faculty of Engineering Universitas Negeri Semarang Semarang Indonesia

ISBN: (数字)9798350368031

ISBN: (纸本)9798350368048

The introduction of autonomous vehicles (AVs) presents a novel approach to regulating and optimising traffic flow through the automated control of AVs. In this context, the AV is defined as the actuator and an optimal control policy is desired to make control decisions. Deep Reinforcement Learning (DRL) is a novel method which aims to maximize the cumulative rewards given by the predefined reward function by making sequential decisions in a stochastic environment. In light of the above, we propose a DRL-based vehicular control method to train an optimal policy for the control of AV in a model-free fashion, and consequently improve the traffic efficiency with the obtained control policy. A single-lane circular road environment with both AV and human-driven vehicles is selected to serve as the mixed autonomy traffic system in the Simulation of Urban MObility (SUMO) [1] traffic simulator, and the Proximal Policy Optimization (PPO) algorithm is applied for the policy improvement. Simulation results demonstrate that our strategy is effective in mitigating the unstable stop-and-go waves, increasing 67.7% of the average driving speed and reducing 19.3% of the average energy consumption in a closed-ring road environment.

关键词： Roads Simulation Heuristic algorithms Stochastic processes Optimal control Deep reinforcement learning Fuels Intelligent systems Traffic congestion Optimization

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Learn to Bid as a Price-Maker Wind Power Producer

arXiv

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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 experimental insight into magnetic flux distribution within the air gap of permanent magnet synchronous drive

Towards experimental insight into magnetic flux distribution...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Hubert Milanowski Adam Krzysztof Piłat Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH University of Krakow Krakow Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

This report explores the experimental identification of magnetic flux density within the motor air gap, focusing on the development of a robot-based approach to automate the scanning procedure. Emphasis is placed on analyzing the distribution of magnetic flux within the motor’s spatial air gap, as well as the amplification of harmonics resulting from changes in air gap orientation. Drawing upon experimental findings, a model is proposed to illustrate the three-dimensional distribution of magnetic flux within the gap.

关键词： Solid modeling Magnetic flux density Automation Atmospheric modeling Air gaps Rotors Drives

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Adaptive Obstacle Avoidance of UAV Leader/Followers with Nonlinear Logarithm Quaternion control

Adaptive Obstacle Avoidance of UAV Leader/Followers with Non...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Huda Naji Al-Sudany Béla Lantos Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

This paper addresses a significant challenge within the realm of fixed wing Unmanned Aerial Vehicles (UAVs), namely obstacle avoidance of the Leader-Follower system. The proposed approach involves formulating the Leader-Follower problem, consisting of one leader and three followers, with control strategies utilizing the logarithm exponential Quaternion method. Subsequently, the designed control law employing quaternions is applied to both the leader and the follower UAVs. Moreover, a notable contribution of this research lies in the incorporation of adaptive obstacle avoidance. The idea based on potential field as obstacle avoidance algorithm, with adaptive techniques for determining obstacle avoidance parameters. These parameters are dynamically adjusted based on the distance between the UAV and the obstacle through a non-linear adaptation function. The comprehensive implementation of these methods is rigorously evaluated by employing a predefined reference path for the leader and conducting numerous scenario-based tests. Random directions of followers were used in case of stuck in local minimum to avoid it; this was applied in case when potential filed force is less than small value. Experiments to test some scenarios of obstacle avoidance were conducted. The final results conclusively demonstrate the stability of the control law even in the presence of obstacles. The effectiveness of the adaptive obstacle avoidance approach is clearly evident from the trajectories of the UAV followers.

关键词： Adaptation models Automation Quaternions Heuristic algorithms Force Autonomous aerial vehicles Stability analysis

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Development of a Method of automatic Single Phase to Earth Fault Current Compensation in Networks with Arc Suppression Coil in Neutral Point 5

Development of a Method of Automatic Single Phase to Earth F...

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5th International Youth Scientific and Technical Conference Relay Protection and Automation, RPA 2022

作者： Kutumov, Yu. D. Shadrikova, T.Yu. Shuin, V.A. Ivanovo State Power Engineering University Jsc so Ups Branch of Ido Center Automatic Control of Electrical Power Systems Department Ivanovo Russia

ISBN: (数字)9798350399912

ISBN: (纸本)9798350399912

At the present time approximately 20% of 6-10 kV cable networks operate with resonant-grounded via arc-suppression coil (ASC) neutral point [1]. Meanwhile, an increasing number of experts note that resonant grounding of neutral point via ASC cannot solve the issue of single phase to earth faults (SPEF) negative consequences and their most dangerous variation, which is called intermittent arc single phase to earth fault (IASPEF) [for example, 2]. The main reasons for the inadequate efficiency of this neutral grounding mode are higher harmonic components in steady-state SPEF current, as well as higher harmonic components which are due to intensive transient processes during SPEF, which cannot be compensates by the usage of ASC. For the compensation of these components it is necessary to apply the devices, which will be complement ASC;these devices, together with the ASC, can be called a system of full compensation of the SPEF current. © 2022 IEEE.

关键词： Electric grounding

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control Strategies for Recommendation Systems in Social Networks

arXiv

引用

arXiv 2024年

作者： Sprenger, Ben De Pasquale, Giulia Soloperto, Raffaele Lygeros, John Dörfler, Florian The Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Physikstrasse 3 Zurich8092 Switzerland

A closed-loop control model to analyze the impact of recommendation systems on opinion dynamics within social networks is introduced. The core contribution is the development and formalization of model-free and model-based approaches to recommendation system design, integrating the dynamics of social interactions within networks via an extension of the Friedkin-Johnsen (FJ) model. Comparative analysis and numerical simulations demonstrate the effectiveness of the proposed control strategies in maximizing user engagement and their potential for influencing opinion formation processes. © 2024, CC BY.

关键词： Recommender systems

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Advanced Signal Processing and Classification of EEG Patterns in Neurointerface Systems 3

Advanced Signal Processing and Classification of EEG Pattern...

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3rd International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2023

作者： Lupenko, Serhii Butsiy, Roman Volyanyk, Oleksandr Stadnyk, Nataliia Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole45-758 Poland Institute of Telecommunications and Global Information Space National Academy of Sciences of Ukraine Kyiv02000 Ukraine Ternopil Ivan Puluj National Technical University Ternopil46001 Ukraine

This study provides a comprehensive assessment of an extended set of modern classifiers designed for electroencephalography signal analysis in brain-computer interface systems. Using the modern model of the vector of cyclic rhythmically connected random processes for estimating signal characteristics, the classifiers compared encompass k-NN, Linear SVM, Decision Tree, Random Forest, Multilayer Perceptron, AdaBoost, and Naive Bayes. By decomposing signals into Fourier series, the optimal number of coefficients is investigated to both reduce computational complexity and increase accuracy. To facilitate a transparent and decisive comparison among the classifiers, the Confusion Matrix methodology is used. Results suggest that among the diverse range evaluated, Linear SVM, Naive Bayes, and Multilayer Perceptron classifiers showcased superior accuracy. © 2023 CEUR-WS. All rights reserved.

关键词： Brain computer interface

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