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arXiv 2025年

作者： Jafari, Seyyed Reza Hansson, Anders Wahlberg, Bo Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-581 83 Sweden Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

Navigating a collision-free, optimal path for a robot poses a perpetual challenge, particularly in the presence of moving objects such as humans. In this study, we formulate the problem of finding an optimal path as a stochastic optimal control problem. However, obtaining a solution to this problem is nontrivial. Therefore, we consider a simplified problem, which is more tractable. For this simplified formulation, we are able to solve the corresponding Bellman equation. However, the solution obtained from the simplified problem does not sufficiently address the original problem of interest. To address the full problem, we propose a numerical procedure where we solve an optimization problem at each sampling instant. The solution to the simplified problem is integrated into the online formulation as a final-state penalty. We illustrate the efficiency of the proposed method using a numerical example. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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Immersive Virtual Reality Cruise Garden Relaxation Train: A Novel BCI Platform for Depression 6th

Immersive Virtual Reality Cruise Garden Relaxation Train: A ...

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6th International Conference on Biomedical and Health Informatics, ICBHI 2024

作者： Tsai, Shu-Hui Chao, Chih-Chiang Lin, Yue-Der Kuo, Chin-Jung Dong, Shu-Ping Liu, Chun-Yuan Ko, Hsin-Yi Wang, Jenn-Hann Liu, Ching Hsiu Service Systems Technology Center Industrial Technology Research Institute Hsin-Chu Taiwan Center for Measurement Standards Industrial Technology Research Institute Hsin-Chu Taiwan Department of Automatic Control Engineering Feng-Chia University Taichung Taiwan Central Division Industrial Technology Research Institute Hsin-Chu Taiwan Mackay Memorial Hospital Hsin-Chu Taiwan

ISBN: (纸本)9783031863226

The staggering global prevalence of depression extends to Taiwan, where approximately 8.9% of the population exhibits symptoms of depression, affecting around 2 million individuals, with 1.25 million classified as severe cases. Depression exerts profound impacts on both socioeconomic and health aspects, ranking as one of the leading causes of disability and closely linked with dementia. Over 70% of suicides involve individuals with depression, and those with depression face significantly higher suicide risks compared to the general population. Of particular concern is the higher-than-expected prevalence of depression, which, if left untreated, may escalate suicide risks. Research indicates that individuals with depression display unstable and imbalanced brainwave patterns, characterized by a lack of normal baseline brainwaves and elevated slow waves. While the commonly used repeated transcranial magnetic stimulation (rTMS) therapy can modulate brainwaves, the treatment is costly and often associated with high relapse rates, imposing a significant burden on patients. Recent studies reveal that potential depression sufferers commonly experience brainwave dysregulation and neuro-immune disruption, emphasizing the need for personalized emotional, brainwave, and autonomic nervous system regulation, along with community support. This study aims to integrate elements such as "Brainwave Entrainment with Schumann Resonance and Autonomic Nervous System Feedback Device", "Light Therapy Device", and "Garden Train-Style Anxiety-Relief Environment" to provide simulated natural environment brainwave and autonomic nervous system regulation, as well as light therapy. Additionally, it involves designing a safe "Garden Train" virtual reality environment to offer a secure and comforting anxiety-relief space for individuals at risk or suffering from depression, as well as caregivers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electrotherapeutics

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System Identification Beyond the Nyquist Frequency: A Kernel-Regularized Approach

arXiv

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arXiv 2025年

作者： van Haren, Max Smith, Roy S. Oomen, Tom Department of Mechanical Engineering Control Systems Technology Section Eindhoven University of Technology Groene Loper 5 Eindhoven5612 AE Netherlands Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland Delft Center for Systems and Control Delft University of Technology Mekelweg 2 Delft2628 CN Netherlands

Models that contain intersample behavior are important for control design of systems with slow-rate outputs. The aim of this paper is to develop a system identification technique for fast-rate models of systems where only slow-rate output measurements are available, e.g., vision-in-the-loop systems. In this paper, the intersample response is estimated by identifying fast-rate models through least-squares criteria, and the limitations of these models are determined. In addition, a method is developed that surpasses these limitations and is capable of estimating unique fast-rate models of arbitrary order by regularizing the least-squares estimate. The developed method utilizes fast-rate inputs and slow-rate outputs and identifies fast-rate models accurately in a single identification experiment. Finally, both simulation and experimental validation on a prototype wafer stage demonstrate the effectiveness of the framework. © 2025, CC BY-NC-ND.

关键词： Decentralized systems

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Investigating the role of an AI-based assistance system for the decision-making process of pilots– an interview study

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Transportation Research Procedia 2025年 88卷 167-175页

作者： Angela Menig Nastassja Becker Johannes P. Kleudgen Technical University Darmstadt Research Group of Work and Engineering Psychology Alexanderstraße 10 64283 Darmstadt Germany Technical University Darmstadt Institute of Flight Systems and Automatic Control Otto-Bernd-Str. 2 64287 Darmstadt Germany

The introduction of cockpit assistance systems based on Artificial Intelligence (AI) hold the potential to significantly increase flight safety and efficiency, especially in complex and time-critical situations. However, there is limited understanding how an AI-based system could effectively assist pilots in the decision-making process. This interview study investigates the decision-making process of pilots in a complex decision-making scenario with and without the support of a Level 1B AI-based assistance system (EASA Roadmap 2.0, 2023). In a complex in-flight diversion scenario, the AI-based assistance system (named Virtual Crew Assistant) provides an assessment of the risks and benefits of suitable alternates in a user-friendly interface, enabling a direct comparison of the given alternates. Semi-standardized expert interviews were conducted with 12 commercial aviation pilots. The pilots were asked to perform a decision-making process for a complex scenario - using the conventional FOR-DEC decision-making model - with and without the support of a static prototype of the Virtual Crew Assistant (VCA). During the decision-making process, the experts were instructed to think aloud, and were also requested to rate the workload for each condition. Working with the AI-based system workload was rated significantly lower than working without the AI-based system. In addition, conditions for Trust, Explainable AI, Usability and Limitations of AI-based assistance systems in the cockpit were investigated. Other possible functions of the AI-based system suggested by the experts are given and extending the human-machine interaction to higher collaborative AI-Levels is discussed.

关键词： AI-based assistance system trustworthiness explainable AI decision-making process reduced crew operations workload

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REGULARIZED HIGHER-ORDER TAYLOR APPROXIMATION METHODS FOR COMPOSITE NONLINEAR LEAST-SQUARES

arXiv

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arXiv 2025年

作者： Nabou, Yassine Necoara, Ion Automatic Control and Systems Engineering Department National University of Science and Technology Politehnica Bucharest Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest Romania

In this paper, we develop a regularized higher-order Taylor based method for solving composite (e.g., nonlinear least-squares) problems. At each iteration, we replace each smooth component of the objective function by a higher-order Taylor approximation with an appropriate regularization, leading to a regularized higher-order Taylor approximation (RHOTA) algorithm. We derive global convergence guarantees for RHOTA algorithm. In particular, we prove stationary point convergence guarantees for the iterates generated by RHOTA, and leveraging a Kurdyka-Lojasiewicz (KL) type property of the objective function, we derive improved rates depending on the KL parameter. When the Taylor approximation is of order 2, we present an efficient implementation of RHOTA algorithm, demonstrating that the resulting nonconvex subproblem can be effectively solved utilizing standard convex programming tools. Furthermore, we extend the scope of our investigation to include the behavior and efficacy of RHOTA algorithm in handling systems of nonlinear equations and optimization problems with nonlinear equality constraints deriving new rates under improved constraint qualifications conditions. Finally, we consider solving the phase retrieval problem with a higher-order proximal point algorithm, showcasing its rapid convergence rate for this particular application. Numerical simulations on phase retrieval and output feedback control problems also demonstrate the efficacy and performance of the proposed methods when compared to some state-of-the-art optimization methods and software. Copyright © 2025, The Authors. All rights reserved.

关键词： Feedback control

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Periodic-Enhanced Informer Model for Short-Term Wind Power Forecasting Using SCADA Data

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IEEE Transactions on Sustainable Energy 2025年

作者： Liu, Zhao-Hua Li, Long-Wei Wei, Hua-Liang Li, Ming Lv, Ming-Yang Zhang, Ying-Jie Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Supervisory control and Data Acquisition (SCADA) systems can collect abundant information about wind farm operation and environment. To better make use of SCADA data, a periodic-enhanced informer model for short-term wind power forecasting using scada data is proposed. Firstly, to effectively filter out noise in SCADA data, a v-p curve-based method is adopted by incorporating a quartile approach to remove sparse outliers;a density-based spatial clustering of applications with noise (DBSCAN) algorithm is then employed to eliminate stacked outliers from the power curve. Secondly, a multi-feature input set selection method based on Maximization Information Coefficient is introduced to make better use of the SCADA system data by reducing the number of features. Thirdly, a Temporal Convolutional Network (TCN) is designed to extract the scalar projection of the input set, followed by fusing the local time stamp and global time stamp to build the periodic information enhanced prediction model embedding layer. Subsequently, the enhanced input set is fed into an informer model to predict future wind power. Finally, considering the multiple temporal scales structure characteristics present in the dataset, a multi-scale deep fusion module is established in the informer model to deeply integrate the features of different scales. It can simultaneously avoid the resource waste and overfitting problems caused by increasing the network depth. The experimental results, which are obtained from several deep learning methods on real SCADA data, demonstrate that the suggested approach has good predictive capability. © 2010-2012 IEEE.

关键词： Wind forecasting

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A Complex-Valued Feedback Linearization-Based controller for a Voltage Source Inverter Tied to the Grid via a Second-Order Filter

arXiv

引用

arXiv 2025年

作者： Tapia-Otaegui, Gerardo Solsona, Jorge A. Jorge, Sebastian Gomez Susperregui, Ana Busada, Claudio A. Itsaso Martínez, M. The Department of Automatic Control and Systems Engineering University of the Basque Country UPV/EHU Faculty of Engineering–Gipuzkoa Donostia20018 Spain UNS-CONICET Departamento de Ingeniería Eléctrica y de Computadoras UNS Bahía Blanca Argentina

In this document, a nonlinear control law for a grid-tied converter is introduced. The converter topology consists of a voltage source inverter (VSI) linked to the grid through an inductive-capacitive second-order filter, its input being connected to a capacitive DC-link supplied by a renewable energy-based input power source. In order to achieve good performance in presence of large state excursions caused mainly by substantial set-point modifications and/or considerable disturbances, a nonlinear control law based on a complex-valued feedback linearization strategy is designed. Specifically, a flat output is adopted, which is given by the summation of the energy stored in the DC-link capacitor and in the output filter’s inductor and capacitor, as well as by the reactive energy at the output. After linearizing the system through a pertinent coordinate transformation and a nonlinear feedback, a linear trajectory tracking control law is implemented. The performance of the system controlled by applying the proposed strategy is tested via simulation for a very weak grid of unity X/R ratio, yielding satisfactory results. © 2025, CC BY-SA.

关键词： Feedback linearization

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A Hybrid Adaptive Filter for Head Tracking in Augmented Reality (AR)-based Flight Simulators

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IEEE Transactions on Computers 2025年

作者： Nwobodo, Onyeka J. Kuaban, Godlove Suila Nkemeni, Valery Wereszczynski, Kamil Cyran, Krzysztof A. Silesian University of Technology Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Polish Academy of Sciences Institute of Theoretical and Applied Informatics Poland University of Buea Laboratory of Electrical Engineering and Computing Faculty of Engineering and Technology Buea Cameroon

This paper presents a novel approach for head tracking in augmented reality (AR) flight simulators using an adaptive fusion of Kalman and particle filters. This fusion dynamically balances the strengths of both algorithms, leveraging Kalman filters for computational efficiency and particle filters for handling non-linearities based on real-time factors such as sensor noise and head movement patterns. Our method demonstrates superior tracking precision and reduced latency, making it particularly effective for immersive pilot training in AR-based flight simulations. While focused on flight simulation, our approach holds high potential for broader applications in other AR and virtual reality (VR) environments where precise, real-time head tracking is crucial. These results provide actionable design guidance for developers optimizing tracking systems in environments that require fast response times and high accuracy. Future extensions of this research could explore the generalization of our approach across diverse AR applications, including human-computer interaction (HCI), medical simulations, and gaming. © 1968-2012 IEEE.

关键词： Flight simulators

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Modeling of Ship Power systems with Semiconductor Propulsion Complexes and Advanced Power Quality Assurance Tools 19th

Modeling of Ship Power Systems with Semiconductor Propulsion...

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19th International Conference on Mathematical Modeling and Simulation of systems, MODS 2024

作者： Zhuk, Dmytro Zhuk, Oleksandr Stepenko, Serhii Chornyi, Oleksii Al-Suod, Mahmoud M. S. Kozlov, Maksym Education and Scientific Institute of Automatics and Electrical Engineering National University of Shipbuilding named after Admiral Makarov Mykolaiv Ukraine Department of Electrical Engineering Information and Measurement Technologies Chernihiv Polytechnic National University Chernihiv Ukraine Department of Automatic Control and Electric Drive Systems Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of Electrical Engineering Al-Ahliyya Amman University Amman19328 Jordan Department of Electrical and Mechatronics Engineering Tafila Technical University Tafila66110 Jordan

ISBN: (纸本)9783031907340

The paper examines possible directions for improving power quality assurance tools by achieving their multifunctionality, controllability, and efficiency, with the aim of enhancing their performance while considering the circuit and operational specifics of integrated ship electrical power systems with semiconductor propulsion complexes. To address the challenges posed by increasing harmonic distortions and reactive power in such systems, one- and two-stage versions of system-controlled filter-compensating devices are proposed and thoroughly investigated. These devices are specifically designed to enable full reactive power compensation while significantly reducing voltage and current harmonic distortions, thus ensuring improved power quality and system reliability in ship electrical power systems with semiconductor propulsion complexes. The proposed modeling approach provides a comprehensive framework for analyzing and comparing the impact of controlled filter-compensating devices on the integral harmonic distortion coefficient of voltage across systems with various types of input rectifiers incorporated within the frequency converters of semiconductor propulsion complexes. Additionally, the study takes into account possible deviations in the ship network frequency, which can influence system performance under real operating conditions. The results demonstrate the effectiveness of the proposed tools in mitigating power quality issues, thereby contributing to the overall stability and efficiency of modern ship electrical power systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Reliability analysis

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Computationally Efficient Optimal control Problem Formulation Illustrated by Automotive Applications 11

Computationally Efficient Optimal Control Problem Formulatio...

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11th Vienna International Conference on Mathematical Modelling, MATHMOD 2025

作者： Wegscheider, F. Galkina, A. Maier, J. Schlacher, K. Reichhartinger, M. Institute of Automation and Control Graz University of Technology Institute of Automation and Control Graz8010 Austria Magna Powertrain GmbH & Co KG Industriestraße 35 Lannach8502 Austria Engineering Center Steyr GmbH & Co KG Steyrer Straße 32 St. Valentin4300 Austria Lehrstuhl für Systemtheorie und Regelungstechnik Universität des Saarlandes Professur für Modellierung und Simulation Technischer Systeme Campus A5 1 Saarbrücken66123 Germany Institute of Automatic Control and Control Systems Technology Johannes Kepler Universität Linz Altenberger Straße 69 Linz4040 Austria

The paper focuses on reducing computational time when solving optimal control problems by expressing them within a flat coordinate system. To demonstrate and discuss this approach, two case studies are presented: Time-optimal velocity trajectory planning and torque control of permanent magnet synchronous motors. The reformulated optimal control problems show significant reductions in computational time without affecting the resulting trajectories. Additionally, analyses were performed to investigate the impact of prediction horizons and solver starting values on the observed computational advantages. The results clearly show the potential of the presented method for developing computationally efficient optimization-based control strategies. Copyright © 2025 The Authors.

关键词： Optimal control systems

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