Proposing an optimal control system specifically focused on the black tea fermentation process
36 viewsDOI:
https://doi.org/10.54939/1859-1043.j.mst.93.2024.30-37Keywords:
Black tea; Optimization; Temperature; Humidity; Color; Decentralized.Abstract
Currently, black tea maintains a significant position in the global beverage market and brings numerous health and cultural benefits. Therefore, quality control of black tea is a matter of concern. In this article, we proposes an optimal control system focused on the black tea fermentation process, based on adjusting temperature and humidity parameters at each stage affecting the quality of black tea. The color change process of tea over time when influenced by temperature and humidity is identified through image analysis at the moment of sudden color change. Regulating humidity and temperature from the humidification system needs to be controlled by electromagnetic valves. The author models the interaction relationship between electromagnetic valves based on graph theory, and an optimal algorithm for steam flow through electromagnetic valves. The proposed results include a theorem and an algorithm, which have been mathematically proven and simulated to ensure control requirements for the quality assurance of black tea.
References
[1]. Akuli, A.; Pal, A.; Dey, T.; Bej, G.; Santra, A.; Majumdar, S.; Bhattacharyya, N. “Assessment of Black Tea Using Low-Level Image Feature Extraction Technique”. Proc. Glob. AI Congr. 20192020, Springer, 453–467. DOI: https://doi.org/10.1007/978-981-15-2188-1_36
[2]. S. Tharaga, B. J. Watawana, W. K. I. L. Wanniarachchi, K.W.S.N.K. and D.D.C.W. “Significance of Physical Parameters to Optimize the Bed Tea Leaves’ Temperature During Fermentation Stage of Black Tea Manufacturing Process”. 2018 IEEE Int. Conf. Inf. Autom. Sustain, Colombo, S, 1–5, (2018). DOI: https://doi.org/10.1109/ICIAFS.2018.8913364
[3]. Mesbahi, Mehran and Magnus Egerstedt. “Graph theoretic methods in multi-agent networks”. Princeton Univ Pr, p. 403. isbn: 9780691140612, (2010). doi: 10.1073/ pnas.0703993104. DOI: https://doi.org/10.1515/9781400835355
[4]. Olfati-Saber, Reza, J Alex Fax, and Richard M Murray. “Consensus and cooperation in networked multi-agent systems”. In: Proceedings of the IEEE 95.1, pp. 215-233. issn: 00189219, (2007). doi: 10.1109/JPROC.2006.887293. arXiv: 1009. 6050. DOI: https://doi.org/10.1109/JPROC.2006.887293
[5]. Zhongkui Li et al. “Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint”. In: IEEE Transactions on Circuits and Systems I: Regular Papers 57.1, pp. 213-224. issn: 1549-8328, (2010). doi: 10.1109/TCSI.2009.2023937. DOI: https://doi.org/10.1109/TCSI.2009.2023937
[6]. Zhong, Y.h.; Zhang, S.; He, R.; Zhang, J.; Zhou, Z.; Cheng, X.; Huang, G.. Z. “A Convolutional Neural Network Based Auto Features Extraction Method for Tea Classification with Electronic Tongue”. Appl. Sci. 9, 2518, (2019). DOI: https://doi.org/10.3390/app9122518
[7]. X. Zhou, Z.T. and F.Q. “Identification of Black Tea Fermentation Degree Based on Convolutional Neural Network”. 2018 Int. Conf. Intell. Auton. Syst, Singapore, 5–8, (2018). DOI: https://doi.org/10.1109/ICoIAS.2018.8494051
[8]. Yang, Z., Tang, J., Xue, L., & Peng, Y. “Study on High Efficiency Black Tea Fermentation Control System Based on Multiple Regression”. 2021 2nd Int. Conf. Artif. Intell. Inf. Syst, Article No, (pp. 1-5), (2021). DOI: https://doi.org/10.1145/3469213.3471321
[9]. D. O. Anderson and J. B. Moore. “Optimal Control: Linear, Quadratic Methods”. Englewood Cliffs, NJ: Prentice Hall, (1990).
