Е-Публикации
Технически университет - София

Abstract: Environmental optimization is a critical aspect of modern resource management, requiring intelligent decision-making systems that can adapt to dynamic conditions. This paper presents a Virtual Instrument-Based Expert System designed to optimize environmental parameters such as energy consumption, water utilization, and climate control. By integrating virtual instruments within an expert system framework, the proposed approach enables real-time data acquisition, analysis, and adaptive decision-making. The system leverages rule-based logic to adjust environmental factors dynamically, ensuring efficient resource utilization while maintaining optimal conditions. A case study implementation in LabVIEW demonstrates the system's ability to monitor and regulate key environmental variables without the need for external hardware. The results highlight the feasibility and effectiveness of virtual instrument-driven expert systems in environmental management, offering a scalable and cost-effective solution for industrial and smart infrastructure applications.

References

1. S. Bolognani, F. C. Lee, and D. Maksimovic, "Digital Control and Optimization Techniques for High-Efficiency Power Converters, " in Proceedings of the IEEE Energy Conversion Congress and Exposition (ECCE), 2018.
2. J. M. Guerrero, M. Malinowski, and S. Lakshmanan, "Trends in Smart Grid Converters: A Review, " in Proceedings of the IEEE Applied Power Electronics Conference and Exposition (APEC), 2019.
3. R. Teodorescu, F. Blaabjerg, and M. Liserre, "Advanced Control Techniques for Power Converters in Renewable Energy Systems, " in Proceedings of the IEEE International Conference on Renewable Energy Integration into Smart Grids (ICREISG), 2017.
4. S. Yu, X. Yang, and H. Wang, "Recent Advances in Wide Bandgap Semiconductor Devices for High-Efficiency Power Converters, " in Proceedings of the IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 2020.
5. J. Kolar and S. D. Round, "Scalable and Modular Designs for Smart Grid Converters, " in Proceedings of the IEEE International Conference on Smart Grid Technologies (ICSGT), 2019.
6. M. Liserre and R. Teodorescu, "Grid-Supportive Features of Smart Power Converters for Renewable Energy Integration, " in Proceedings of the IEEE International Conference on Clean Energy and Technology (ICCET), 2018.
7. S. B. Han, Y. Yu, and F. C. Lee, "Advances in Power Conversion and Control Techniques for Wind Energy Systems, " in Proceedings of the IEEE International Conference on Power Electronics and Renewable Energy Systems (ICPERES), 2016.
8. N. Kularatna and S. Perera, "Challenges and Opportunities in Power Electronics for Smart Grid Applications, " in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), 2019.
9. I. Batarseh, M. Bataresh, and M. Arafat, "Cybersecurity Considerations in Smart Power Converters for Industrial Applications, " in Proceedings of the IEEE International Conference on Industrial Electronics (IECON), 2017.
10. X. Yu, H. Choi, and Z. Wang, "Integration of Digital Control Techniques in Power Electronics for Improved Efficiency and Performance, " in Proceedings of the IEEE International Conference on Power Electronics and Energy Conversion Systems (PEECS), 2018.
11. K. Ogata, Modern Control Engineering, 5th ed. Upper Saddle River, NJ: Pearson Education, 2010.
12. R. S. Pressman, Software Engineering: A Practitioner's Approach, 7th ed. New York, NY: McGraw-Hill, 2010.
13. National Instruments, "LabVIEW Documentation and Manuals, " [Online]. Available: Https: //www. ni. com/documentation

Issue

Copyright IEEE