iosr-JEEE   Volume-20 ~ Issue-4 ~ July – Aug. 2025

Abstract: This work presents the effectiveness of a Lorentz torque-based feedback controller in mitigating wind gust–induced vibrations in wind turbine blades. A mathematical model of performance evaluation of Lorentz torque controller for vibration suppression was developed and implemented in the MATLAB/ Simulink environment, incorporating turbine generator...

Key Word: Wind turbine vibration, Lorentz torque, MATLAB/Simulink, blade dynamics, wind gust, active damping, control systems

[1] Beskhyroun, S., Wegner, L. D., & Sparling, B. F. (2011). Integral Resonant Control Scheme For Cancelling Human-Induced Vibrations In Light-Weight Pedestrian Structures. Structural Control And Health Monitoring, May 2011, N/A-N/A. Https://Doi.rg/10.1002/Stc
[2] Bin, G., Li, X., Shen, Y., & Wang, W. (2018). Development Of Whole-Machine High Speed Balance Approach For Turbomachinery Shaft System With N + 1 Supports. Measurement: Journal Of The International Measurement Confederation, 122(May 2016), 368–379. Https://Doi.Org/10.1016/J.Measurement.2018.02.035
[3] Chong, C. H., Rigit, A. R. H., & Ali, I. (2021). Wind Turbine Modelling And Simulation Using Matlab / SIMULINK. IOP Conference Series: Materials Science And Engineering, 1101(1), 012034. Https://Doi.Org/10.1088/1757-899x/1101/1/012034
[4] Elhaji, E. M. (2018). Modeling And Control Of Wind Turbine To Damp The Power Oscillation. Stability Control And Reliable Performance Of Wind Turbines. Https://Doi.Org/10.5772/Intechopen.74835
[5] Fitzgerald, B., Basu, B., & Nielsen, S. R. K. (2013). Active Tuned Mass Dampers For Control Of In-Plane Vibrations Of Wind Turbine Blades. January, 1377–1396. Https://Doi.Org/10.1002/Stc.

Abstract: Electric vehicles (EVs) have revolutionized the automotive industry by offering an environmentally friendly alternative to traditional combustion engines, and their electrical systems are a pivotal aspect of this transformation. A critical component within these systems is the use of precharge and discharge resistors. These resistors play a vital role in managing the high voltage circuits integral to EV operation, ensuring both safety and efficiency. Their function is particularly crucial during the initial power up phase and when the vehicle is turned off, as they regulate the current flow to prevent damage to sensitive electronic components. Precharge resistors..

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Abstract: Background: Achieving a sustainable and environmentally friendly power generating system has become a major challenge in both the public and private sectors of developing nations. Several effort has been put in place and painstaking research had been done in various institutions and laboratories for solutions to this mind bouging issue of inadequate power supply and environmental degradation occasioned by the continious release of green-house gas into the atmosphere. Most institutions of higher learning as well as public and private enterprises in Nigeria are faced......

Key Word: Solar energy, Hybrid, Generation, Model, Renewable, Central receiver, Gas turbine

[1]. Anyaehie M. U. “Power & Energy And National Development”, 2nd Annual Conference Journal Of School Of Business & Management Technology (SBMT), Federal Polytechnic Nekede, Nigeria. 2009;1(1):146-154.
[2]. Manzoore, E. M., Soudagar, S. S., Deepali, M., Pramod, B., Mohammad, Nur-E-Alam, Tiong, S. K., Ramesh, S., Armin, R., Harish, V., Yunus, K. T. M, Mujtaba, M. A., Kiran, S., Kalam, M. A., Fattah, I.M.R. Optimizing IC Engine Efficiency: A Comprehensive Review On Biodiesel, Nanofluid, And The Role Of Artificial Intelligence And Machine Learning, Energy Conversion And Management, 2024;307: 118337,
[3]. Deshmukh, M. K. And Deshmukh, S. S. Modeling Of Hybrid Renewable Energy Systems. Renewable And Sustainable Energy Reviews, Elsevier Ltd, 2008; 12: 235–249.
[4]. Abshishek, R. Introduction To ANN (Artificial Neural Networks) Set 3 (Hybrid Systems) Www.Geeksforgeeks.Org/Introduction-Ann-Artificial-Neural-Networks-Set-3-Hybrid-Systems/#Article-Meta-Div, Accessed On July 14, 2023

Abstract: It is well known that in many control applications, the hysteresis can be taken advantage of to provide an easy and accurate solution for control purposes. In this paper, the automation of a hysteresis window controlling system is presented. Different solutions, such as classical digital control, block diagram functions, ladder diagrams, and on-off relays’ modules, were implemented by engineering college students, showing students' interest and establishing a solid foundation for their technical training and understanding of automatic control techniques.......

[1] Yang, J., Ma, X., Fei, L., Zhang, X., Luo, K. H., & Shuai, S. (2020). Effects Of Hysteresis Window On Contact Angle Hysteresis Behaviour At Large Bond Number. Journal Of Colloid And Interface Science, 566, 327-337.
[2] Yoon, C., Moon, S., & Shin, C. (2020). Study Of A Hysteresis Window Of Finfet And Fully-Depleted Silicon-On-Insulator (FDSOI) MOSFET With Ferroelectric Capacitor. Nano Convergence, 7(1), 19.
[3] Huang, H. H., Chen, C. L., & Chen, K. H. (2009). Adaptive Window Control (AWC) Technique For Hysteresis DC–DC Buck Converters With Improved Light And Heavy Load Performance. IEEE Transactions On Power Electronics, 24(6), 1607-1617.
[4] Jo, J., & Shin, C. (2016). Negative Capacitance Field Effect Transistor With Hysteresis-Free Sub-60-Mv/Decade Switching. IEEE Electron Device Letters, 37(3), 245-248.
[5] Sol, C., Schläfer, J., Parkin, I. P., & Papakonstantinou, I. (2018). Mitigation Of Hysteresis Due To A Pseudo-Photochromic Effect In Thermochromic Smart Window Coatings. Scientific Reports, 8(1), 13249.

Abstract: Metal surface defect detection plays a critical role in automatic quality control systems for metal manufacturing industries. This study proposes an automated defect classification approach using a Sequential Neural Network model. The performance of five activation functions, such as Rectified Linear Unit (ReLU), Leaky ReLU (LReLU), Swish, Mish, and Exponential Linear Squashing (ELiSH), was evaluated based on classification accuracy, precision, recall, loss, confusion matrices, and learning curve behavior. The publicly available NEU Metal Surface Defect.......

Keywords: Activation function, convolutional neural network, defect detection, metal surface, Mish

[1] J. Jiang, C. Li, X. Zhang, J. Wang, And C. Liu, "Surface Defect Detection Of High Precision Cylindrical Metal Parts Based On Machine Vision," In Proc. Intelligent Robotics And Applications (Icira), Lecture Notes In Computer Science, Vol. 13014, Pp. 810–820, Cham, Switzerland: Springer, 2021.
[2] Z. Li, X. Wei, M. Hassaballah, Y. Li, And X. Jiang, “A Deep Learning Model For Steel Surface Defect Detection,” Complex & Intelligent Systems, Vol. 10, Pp. 885–897, 2024.
[3] V. Nair And G. E. Hinton, “Rectified Linear Units Improve Restricted Boltzmann Machines,” In Proc. 27th Int. Conf. On Machine Learning (Icml), Haifa, Israel, 2010, Pp. 807–814.
[4] A. L. Maas, A. Y. Hannun, And A. Y. Ng, “Rectifier Nonlinearities Improve Neural Network Acoustic Models,” In Proc. 30th Int. Conf. On Machine Learning (Icml), Vol. 28, 2013.
[5] P. Ramachandran, B. Zoph, And Q. V. Le, “Searching For Activation Functions,” Arxiv Preprint Arxiv:1710.05941, 2017..

Abstract: This paper presents the development and simulation of a real-time, crop-specific, feedback-driven irrigation and fertilization management system designed to optimize the use of limited water and nutrient resources. Implemented using MATLAB Simulink and Python 3.7, the system integrates simulated multi-sensor inputs, PID controller, fuzzy inference, and actuator modeling to dynamically adjust irrigation and fertigation schedules based on soil moisture, nutrient content, temperature, and crop growth stages. An artificial neural network trained via transfer......

Keywords: Precision irrigation, fertigation, fuzzy logic, PID control, artificial neural networks, MATLAB Simulink.

[1] Bhatti, S., Heeren, D. M., O’Shaughnessy, S. A., Neale, C.M.U., Larue, J., Melvin, S., Wilkening, E., & Bai, G. (2023). Toward Automated Irrigation Management With Integrated Crop Water Stress Index And Spatial Soil Water Balance. Precision Agriculture, 24, 2223–2247. Https://Doi.Org/10.1007/S11119-023-10038-4
[2] Evans, R. G., Larue, J., Stone, K. C., & King, B. A. (2013). Adoption Of Site-Specific Variable Rate Sprinkler Irrigation Systems. Irrigation Science, 31, 871–887.
[3] García, L., Parra, L., Jimenez, J. M., Lloret, J., & Lorenz, P. (2020). Iot-Based Smart Irrigation Systems: An Overview On The Recent Trends. Journal Of Network And Computer Applications, 20(4). Https://Doi.Org/10.3390/S20041042
[4] Gu, Z., Qi, Z., Burghate, R., Yuan, S., Jiao, X., & Xu, J. (2020). Irrigation Scheduling Approaches And Applications: A Review. Journal Of Irrigation And Drainage Engineering, 146(6). Https://Doi.Org/10.1061/(ASCE)IR.1943-4774.0001464
[5] Mishra, P., Kumar, A., & Singh, S. (2021). Iot-Based Automated Irrigation System For Water Conservation. International Journal Of Agricultural Engineering, 14(2), 67–75