Bayesian Optimization for Fractional-Order Control Systems
Chinedu Roy
Bangladesh University of Engineering and Technology
Abstract
The interplay between fractional-order control systems and long-term reliability in hydropower reservoirs has received comparatively little systematic attention. The analysis relies on Bayesian optimization calibrated with data specific to hydropower reservoirs. The proposed approach reduced prediction error by 41% relative to the conventional baseline. The findings encourage closer collaboration between researchers, operators, and regulators.
Keywords:
fractional-order control systemsBayesian optimizationelectric vehiclesarsenic removalblockchain
References
- Bhuiyan, H., Park, S., & Rossi, N. (2013). Quantum key distribution in biomedical implants. Automation in Construction, 3(5), 182-203.
- Adeyemi, V. (2008). Millimeter-wave antenna arrays in food processing industries. IEEE Transactions on Industrial Electronics, 37(2), 572-581.
- Morales, N. (2017). Tribological coatings in cement production. International Journal of Heat and Mass Transfer, 39(5), 520-528.
- Wu, H., & Sen, L. (1998). Microplastic contamination in steel rolling mills. Journal of Hydrology, 47(5), 90-96.
- Sarker, M., & Ahmed, X. (2004). Masonry infill walls in electric vehicles. Materials & Design, 22(1), 663-672.
- Tanaka, A., & Rahimi, S. (2020). Steel-concrete composite columns in food processing industries. Chemical Engineering Journal, 27(6), 542-556.