TY - JOUR AU - Kovács, Adorján AU - Vajk, István TI - Internal Model-Based Robust Path-Following Control for Autonomous Vehicles JF - INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY J2 - INT J AUTOMOT TECHN VL - 25 PY - 2024 IS - 2 SP - 249 EP - 260 PG - 12 SN - 1229-9138 DO - 10.1007/s12239-024-00003-z UR - https://m2.mtmt.hu/api/publication/34735212 ID - 34735212 N1 - Export Date: 18 March 2024 Correspondence Address: Vajk, I.; Department of Automation and Applied Informatics, Műegyetem rkp. 3., Hungary; email: vajk@aut.bme.hu AB - The paper presents a new internal model control (IMC) based control technique for lateral trajectory tracking of autonomous vehicles. The controller’s proposed structure employs a robust, fault-tolerant nonlinear internal servo control with optimal reference generation concerning vehicle yaw stability and physical limitations. The presented inscription of the reference generation creates a convex optimization task that can be used in real-time applications. Improvements in yaw-rate stability of vehicle motion control are first shown through simulation results performed in a Simulink environment. The controller structure was also implemented in a real-time model and was examined in a Mercedes C-Class vehicle. In this article, the simulation results and the real-time measurements are presented. The results show that the proposed controller has high efficiency in disturbance rejection and lower sensitivity towards parameter changes compared to a model predictive control (MPC) structure. LA - English DB - MTMT ER - TY - JOUR AU - AL-Magsoosi, Husam Kareem Farhan AU - Dunaev, Dmitriy TI - A Novel Low Hardware Configurable Ring Oscillator (CRO) PUF for Lightweight Security Applications JF - MICROPROCESSORS AND MICROSYSTEMS J2 - MICROPROCESS MICROSY VL - 104 PY - 2024 PG - 10 SN - 0141-9331 DO - 10.1016/j.micpro.2023.104989 UR - https://m2.mtmt.hu/api/publication/34450400 ID - 34450400 N1 - Export Date: 12 January 2024 CODEN: MIMID Correspondence Address: Kareem, H.; Department of Automation and Applied Informatics, Műegyetem rkp. 3, Hungary; email: hus_almagsoosi@edu.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Alsarayreh, Saif AU - Sütő, Zoltán TI - Optimal Selection of Switch Model Parameters for ADC-Based Power Converters JF - ENERGIES J2 - ENERGIES VL - 17 PY - 2024 IS - 1 PG - 18 SN - 1996-1073 DO - 10.3390/en17010056 UR - https://m2.mtmt.hu/api/publication/34448114 ID - 34448114 N1 - Export Date: 19 January 2024 Correspondence Address: Alsarayreh, S.; Department of Automation and Applied Informatics, Műegyetem rkp. 3, Hungary; email: saif.alsarayreh@aut.bme.hu Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding text 1: The research reported in this paper is part of project no. BME-NVA-02, implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021 funding scheme. AB - Real-time hardware-in-the-loop-(HIL) simulation integration is now a fundamental component of the power electronics control design cycle. This integration is required to test the efficacy of controller implementations. Even though hardware-in-the-loop-(HIL) tools use FPGA devices with computing power that is rapidly evolving, developers constantly need to balance the ease of deploying models with acceptable accuracy. This study introduces a methodology for implementing a full-bridge inverter and buck converter utilising the associate-discrete-circuit-(ADC) model, which is optimised for real-time simulator applications. Additionally, this work introduces a new approach for choosing ADC parameter values by using the artificial-bee-colony-(ABC) algorithm, the firefly algorithm (FFA), and the genetic algorithm (GA). The implementation of the ADC-based model enables the development of a consistent architecture in simulation, regardless of the states of the switches. The simulation results demonstrate the efficacy of the proposed methodology in selecting optimal parameters for an ADC-switch-based full-bridge inverter and buck converter. These results indicate a reduction in overshoot and settling time observed in both the output voltage and current of the chosen topologies. LA - English DB - MTMT ER - TY - JOUR AU - AL-Magsoosi, Husam Kareem Farhan AU - Dunaev, Dmitriy TI - A Robust Architecture of Ring Oscillator PUF: Enhancing Cryptographic Security with Configurability JF - MICROELECTRONICS JOURNAL J2 - MICROELECTRON J VL - 143 PY - 2024 PG - 9 SN - 0026-2692 DO - 10.1016/j.mejo.2023.106022 UR - https://m2.mtmt.hu/api/publication/34415932 ID - 34415932 LA - English DB - MTMT ER - TY - JOUR AU - Erdős, Szilvia AU - Kővári, Bence András TI - Exploring fair scheduling aspects-Through final exam scheduling JF - POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES J2 - POLLACK PERIODICA VL - 19 PY - 2024 IS - 1 SP - 151 EP - 156 PG - 6 SN - 1788-1994 DO - 10.1556/606.2023.00780 UR - https://m2.mtmt.hu/api/publication/34342470 ID - 34342470 N1 - Export Date: 16 November 2023 Correspondence Address: Jáhn-Erdos, S.; Department of Automation and Applied Informatics, Hungary; email: Erdos.Szilvia@aut.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Ács, Judit AU - Hamerlik, Endre AU - Schwartz, Roy AU - Smith, Noah A. AU - Kornai, András TI - Morphosyntactic probing of multilingual BERT models JF - NATURAL LANGUAGE ENGINEERING J2 - NAT LANG ENG PY - 2024 SP - 1 EP - 40 PG - 40 SN - 1351-3249 DO - 10.1017/S1351324923000190 UR - https://m2.mtmt.hu/api/publication/33999207 ID - 33999207 N1 - Funding Agency and Grant Number: European Union [RRF-2.3.1-21-2022-00004]; Fulbright Scholarship; Rosztoczy Scholarship; Slovak Research and Development Agency [APVV-21-0114, 52110970] Funding text: We are grateful for the anonymous reviewers' insightful criticism, inquiries that prompted more discussion in the text, and high-quality references. This work was partially supported by the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory Grant no RRF-2.3.1-21-2022-00004. Judit Acs was partially supported by the Fulbright Scholarship and the Rosztoczy Scholarship. Endre Hamerlik was partially supported by grant APVV-21-0114 of the Slovak Research and Development Agency and Visegrad Scholarship nr.: 52110970. AB - We introduce an extensive dataset for multilingual probing of morphological information in language models (247 tasks across 42 languages from 10 families), each consisting of a sentence with a target word and a morphological tag as the desired label, derived from the Universal Dependencies treebanks. We find that pre-trained Transformer models (mBERT and XLM-RoBERTa) learn features that attain strong performance across these tasks. We then apply two methods to locate, for each probing task, where the disambiguating information resides in the input. The first is a new perturbation method that “masks” various parts of context; the second is the classical method of Shapley values. The most intriguing finding that emerges is a strong tendency for the preceding context to hold more information relevant to the prediction than the following context. LA - English DB - MTMT ER - TY - CHAP AU - CHOWDHURY, MD MOSHIUR AU - Sütő, Zoltán ED - Vajk, István ED - Dunaev, Dmitriy TI - The survey of FPGA-based Hardware-In-The-Loop (HIL) simulation in Control Systems and Power Electronics T2 - Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23) PB - Budapesti Műszaki Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék CY - Budapest SN - 9789634219262 PY - 2023 SP - 103 EP - 114 PG - 12 UR - https://m2.mtmt.hu/api/publication/34835609 ID - 34835609 LA - English DB - MTMT ER - TY - CHAP AU - Szinyéri, Bence AU - Kővári, Bence András TI - Comparison of a Deep Learning-based Axle Load Estimator and the Matrix Method in Strain Gauge-based Bridge Weigh-In-Motion Systems T2 - 2023 10th International Conference on Soft Computing & Machine Intelligence (ISCMI) PB - IEEE CY - Piscataway (NJ) SN - 9798350359374 T3 - International Conference on Soft Computing & Machine Intelligence ISCMI, ISSN 2640-0154 PY - 2023 SP - 12 EP - 16 PG - 5 DO - 10.1109/ISCMI59957.2023.10458514 UR - https://m2.mtmt.hu/api/publication/34763429 ID - 34763429 N1 - Conference code: 198042 Export Date: 2 April 2024 AB - One aspect of structural health monitoring of bridges is to monitor vehicular traffic. The demand for moni-toring bridge performance and life cycle has led to measuring traffic flow. We have previously developed a deep learning-based axle load estimator showing promising results considering COST 323 benchmark. This paper compares the deep learning-based solution to the established matrix method under different circumstances. Results show that the deep learning-based solution achieves better accuracy on several datasets of the BME-Simulated I corpus and has a better ability to handle noise than the matrix method. © 2023 IEEE. LA - English DB - MTMT ER - TY - CHAP AU - Somogyi, Norbert ED - Vajk, István ED - Dunaev, Dmitriy TI - Towards Abstraction-Based Formal Verification of Static Modeling Constraints T2 - Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23) PB - Budapesti Műszaki Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék CY - Budapest SN - 9789634219262 PY - 2023 SP - 174 EP - 185 PG - 12 UR - https://m2.mtmt.hu/api/publication/34693431 ID - 34693431 LA - English DB - MTMT ER - TY - CHAP AU - Shubbar, Mustafa AU - Rakos, Balázs ED - Vajk, István ED - Dunaev, Dmitriy TI - Application of spherical lenses for efficiency enhancement of rectenna-based IR energy harvesting systems T2 - Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23) PB - Budapesti Műszaki Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék CY - Budapest SN - 9789634219262 PY - 2023 SP - 76 EP - 82 PG - 7 UR - https://m2.mtmt.hu/api/publication/34689965 ID - 34689965 LA - English DB - MTMT ER -