Prof William Holderbaum's Outputs (12)

Advanced voltage relay design for distance relay coordination in power networks equipped with low‐inertia areas (2024)
Journal Article
Alasali, F., El‐Naily, N., Mustafa, H. Y., Loukil, H., Saad, S. M., Saidi, A. S., & Holderbaum, W. (2024). Advanced voltage relay design for distance relay coordination in power networks equipped with low‐inertia areas. IET Generation, Transmission and Distribution, 19, Article e13338. https://doi.org/10.1049/gtd2.13338

In modern power systems with high levels of distributed generation (DG), traditional protection schemes face challenges in ensuring reliable and efficient fault detection due to the complexities introduced by DG, particularly low‐inertia sources such... Read More about Advanced voltage relay design for distance relay coordination in power networks equipped with low‐inertia areas.

Time parametrized motion planning (2024)
Journal Article
Taylor, S., Linton, C., Biggs, J., & Holderbaum, W. (2024). Time parametrized motion planning. Mathematics, 12(21), 3404. https://doi.org/10.3390/math12213404

Time can be treated as a free parameter to isotropically stretch the tangent space. A trajectory, which matches the boundary conditions on its configuration, is adjusted so that velocity conditions are met. The modified trajectory is found by substit... Read More about Time parametrized motion planning.

A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots (2024)
Journal Article
Amiri, P., Müller, M., Southgate, M., Theodoridis, T., Wei, G., Richards-Brown, M., & Holderbaum, W. (2024). A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots. #Journal not on list, 8(5), 216. https://doi.org/10.3390/jmmp8050216

This paper aims to elucidate the state-of-the-art, prevailing priorities, and the focus of the industry, and identify both limitations and potential gaps regarding industrial robots and collaborative robots (cobots). Additionally, it outlines the adv... Read More about A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots.

Innovative protection schemes through hardware-in-the-loop dynamic testing. (2024)
Journal Article
Alasali, F., El-Naily, N., Y. Mustafa, H., Loukil, H., M. Saad, S., Salah Saidi, A., & Holderbaum, W. (2024). Innovative protection schemes through hardware-in-the-loop dynamic testing. Computers and Electrical Engineering, 119(Part B), Article 109559. https://doi.org/10.1016/j.compeleceng.2024.109559

In microgrid environments, the behaviour of Distributed Generation (DG) during fault conditions
varies significantly based on DG types and penetration levels. Conventional Overcurrent Relays
(OCRs) with standard time-current characteristics may exh... Read More about Innovative protection schemes through hardware-in-the-loop dynamic testing..

Highly sensitive protection scheme considering the PV operation control models (2024)
Journal Article
Alasali, F., Albayadrah, H., El-Naily, N., Loukil, H., Holderbaum, W., Flah, A., & Saidi, A. S. (in press). Highly sensitive protection scheme considering the PV operation control models. Electric Power Systems Research, 237, Article 111025. https://doi.org/10.1016/j.epsr.2024.111025

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanis... Read More about Highly sensitive protection scheme considering the PV operation control models.

A Novel Approach for Solving the Time-Varying Complex-Valued Linear Matrix Inequality Based on Fuzzy-Parameter Zeroing Neural Network (2024)
Conference Proceeding
Luo, J., Li, J., Holderbaum, W., & Li, J. (2024). A Novel Approach for Solving the Time-Varying Complex-Valued Linear Matrix Inequality Based on Fuzzy-Parameter Zeroing Neural Network. In 2024 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM) (543-548). https://doi.org/10.1109/cis-ram61939.2024.10672985

Solving linear matrix inequality (LMI) is crucial across diverse fields, and the emergence of zeroing neural networks (ZNN) presents a novel solution for the time-varying LMI (TV-LMI) challenge. However, the application of ZNN to solve the time-varyi... Read More about A Novel Approach for Solving the Time-Varying Complex-Valued Linear Matrix Inequality Based on Fuzzy-Parameter Zeroing Neural Network.

Approaches for Enhancement of Perception Through Snsor Design for Extreme Environment (2024)
Conference Proceeding
Li, J., Li, N., Holderbaum, W., & Yao, W. (2024). Approaches for Enhancement of Perception Through Snsor Design for Extreme Environment. In 2024 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM) (531-536). https://doi.org/10.1109/cis-ram61939.2024.10672968

The application of artificial intelligence (AI) and robotics in extreme environments, is crucial for addressing complex challenges and performing high risk tasks. We highlight the importance of multi-modal sensor redundancy to ensure system reliabili... Read More about Approaches for Enhancement of Perception Through Snsor Design for Extreme Environment.

Challenges in the Guidance, Navigation and Control of Autonomous and Transport Vehicles (2024)
Journal Article
Horri, N., Holderbaum, W., & Giulietti, F. (in press). Challenges in the Guidance, Navigation and Control of Autonomous and Transport Vehicles. Applied Sciences, 14(15), Article 6635. https://doi.org/10.3390/app14156635

Advanced Optimal Twin‐Setting Protection Coordination Scheme for Maximizing Microgrid Resilience (2024)
Journal Article
Alasali, F., El-Naily, N., Saidi, A., Nasr A. Elghaffar, A., & Holderbaum, W. (2024). Advanced Optimal Twin‐Setting Protection Coordination Scheme for Maximizing Microgrid Resilience. International Journal of Energy Research, 2024, Article 276352. https://doi.org/10.1155/2024/7276352

The increasing penetration of distribution generators (DGs), such as PV systems, has led to a significant power protection concern
for optimal overcurrent coordination. However, existing literature indicates that the traditional phase over current re... Read More about Advanced Optimal Twin‐Setting Protection Coordination Scheme for Maximizing Microgrid Resilience.

Enhancing Gearbox Fault Diagnosis through Advanced Feature Engineering and Data Segmentation Techniques (2024)
Journal Article
Shukla, K., Holderbaum, W., Theodoridis, T., & Wei, G. (in press). Enhancing Gearbox Fault Diagnosis through Advanced Feature Engineering and Data Segmentation Techniques. Machines, 12(4), 261. https://doi.org/10.3390/machines12040261

Efficient gearbox fault diagnosis is crucial for the cost-effective maintenance and reliable operation of rotating machinery. Despite extensive research, effective fault diagnosis remains challenging due to the multitude of features available for cla... Read More about Enhancing Gearbox Fault Diagnosis through Advanced Feature Engineering and Data Segmentation Techniques.

Enhancing resilience of advanced power protection systems in smart grids against cyber–physical threats (2024)
Journal Article
Alasali, F., Hayajneh, A. M., Ghalyon, S. A., El‐Naily, N., AlMajali, A., Itradat, A., …Zaroure, E. (in press). Enhancing resilience of advanced power protection systems in smart grids against cyber–physical threats. IET Renewable Power Generation, https://doi.org/10.1049/rpg2.12957

Recently, smart grids introduce significant challenges to power system protection due to the high integration with distributed energy resources (DERs) and communication systems. To effectively manage the impact of DERs on power networks, researchers... Read More about Enhancing resilience of advanced power protection systems in smart grids against cyber–physical threats.

Intelligent Solar Forecasts: Modern Machine Learning Models and TinyML Role for Improved Solar Energy Yield Predictions (2024)
Journal Article
Hayajneh, A. M., Alasali, F., Salama, A., & Holderbaum, W. (2024). Intelligent Solar Forecasts: Modern Machine Learning Models and TinyML Role for Improved Solar Energy Yield Predictions. IEEE Access, 12, 10846-10864. https://doi.org/10.1109/access.2024.3354703

The advancement of sustainable energy sources necessitates the development of robust forecasting tools for efficient energy management. A prominent player in this domain, solar power, heavily relies on accurate energy yield predictions to optimize pr... Read More about Intelligent Solar Forecasts: Modern Machine Learning Models and TinyML Role for Improved Solar Energy Yield Predictions.