journal article·2023-06-06Open access

Temperature Regulation of Hot Vapor Preservation Treatment of Litchi Based on PSO-Fuzzy PID

Hao Tang, Ruijun Ma, Yu Chen, Li Huang, Rui Jiao

Applied Sciences· Volume 13· Issue 12

Abstract

In this paper, a control method was designed based on particle swarm optimization (PSO)–fuzzy PID (PSO-Fuzzy PID). In order to address the issues of significant nonlinearity and extensive hysteresis in the vapor temperature of litchi hot vapor preservation treatment equipment, as well as the inadequacy of traditional control schemes, a PSO-Fuzzy PID controller was developed through the integration of particle swarm optimization and fuzzy logic algorithms. This controller incorporates a scale factor and quantization factor, building upon the foundation of the Fuzzy PID controller. Additionally, a transfer function model was established for both the heating and disturbance links, utilizing a combination of test data modeling methods and relevant theory. Thirdly, a system simulation model was built to compare and verify PID, Fuzzy PID, and PSO-Fuzzy PID control methods, which were carried out on the MATLAB/Simulink simulation platform. Finally, the litchi load test was conducted to further verify the control performance of the PSO-Fuzzy PID method, where the litchi variety was “Jinggang Hongnuo”. The simulation results showed that the overshoot of the optimized control system was reduced by 93.5% and 42.9% compared with the traditional PID control and Fuzzy PID, and the regulation time was shortened by 46% and 31%, which indicates a better control effect. The test results showed that PSO-Fuzzy PID showed better system stability and accuracy than the fuzzy PID control method in different processing temperature and processing time for litchi’s hot vapor treatment. The maximum temperature difference decreased by 0.56 °C on average and the interference adjustment time was reduced by 7.5 s on average. PSO-Fuzzy PID has a good control effect on the temperature of litchi hot vapor treatment, which can provide a reference for model building and temperature control of other similar fruit and vegetable heat treatment equipment.
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Research context

OpenAlex topics: Advanced Algorithms and Applications · Advanced Control Systems Optimization · Postharvest Quality and Shelf Life Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Engineering, South China Agricultural University, Guangzhou 510642, China

Funding

Guangdong Provincial Key Laboratory of Agricultural Artificial Intelligence

References (30)

Show source-provided references
1. Analysis of the production situation for litchi in main planting areas of China in 2020
2. Jiang, Y., Ai, J.W., and Wang, L.L. (2016). Research Progress on Postharvest Preservation Technology of Tropical Fruit Litchi and Longan. Agric. Prod. Process., 63–66. (In Chinese).
3. Yahia, E.M. (2011). Postharvest Biology and Technology of Tropical and Sub-Tropical Fruits, Woodhead Publishing.10.1533/9780857092762 ↗
4. Reduction in activity/gene expression of anthocyanin degradation enzymes in lychee pericarp is responsible for the color protection of the fruit by heat and acid treatment10.1016/S2095-3119(13)60410-4 ↗
5. Postharvest characteristics and handling of litchi fruit—An overview10.1071/EA05108 ↗
6. Internet of things for smart farming and frost intelligent control in greenhouses10.1016/j.compag.2020.105614 ↗
7. A fast and elitist multiobjective genetic algorithm: NSGA-II. Evolutionary Computation
8. Lambora, A., Gupta, K., and Chopra, K. (2019, January 14–16). Genetic algorithm-A literature review. Proceedings of the 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon), Faridabad, India.10.1109/COMITCon.2019.8862255 ↗
9. Energy management strategy of hybrid energy storage system for electric vehicles based on ge-netic algorithm optimization and temperature effect10.1016/j.est.2022.104314 ↗
10. Jain, M., Saihjpal, V., Singh, N., and Singh, S.B. (2022). An Overview of Variants and Advancements of PSO Algorithm. Appl. Sci., 12.10.3390/app12178392 ↗
11. Modeling and optimization of environment in agricultural greenhouses for improving cleaner and sustainable crop production10.1016/j.jclepro.2020.124843 ↗
12. Design and implementation of discrete Jaya and discrete PSO algorithms for auto-matic collaborative learning group composition in an e-learning system10.1016/j.asoc.2022.109611 ↗
13. Dorigo, M., and Stützle, T. (2019). Ant Colony Optimization: Overview and Recent Advances, Springer.10.1007/978-3-319-91086-4_10 ↗
14. Montalvo, W., Guanochanga, D., and Chapaca, J. (2022). Communication, Smart Technologies and Innovation for Society, Springer.
15. Jia, Y. (2015). Research on Human-simulated Intelligent Control based on Genetic Optimization in Temperature Control System. New Technol. New Process, 106–109. (In Chinese).
16. Control Parameter Tuning Based on Genetic Algorithm and Its Application in Temperature Control
17. Saini, S., and Rani, S. (2012, January 7–8). Temperature Control Using Intelligent Techniques. Proceedings of the 2012 Second International Conference on Advanced Computing & Communication Technologies, Rohtak, India.10.1109/ACCT.2012.110 ↗
18. Optimization based on PSO-ANFIS in Water bath Temperature System
19. Adnan, R., Tajjudin, M., Ishak, N., Ismail, H., Rahiman, M.H.F., and Arshad, N.M. (2012, January 11–12). Comparison between self-tuning Fuzzy-PID and Pole-Placement PID with application to saturated steam temperature regulation. Proceedings of the 2012 International Conference on System Engineering and Technology (ICSET), Bandung, Indonesia.10.1109/ICSEngT.2012.6339283 ↗
20. Gouadria, F., Sbita, L., and Sigrimis, N. (2017, January 23–25). A greenhouse system control based on a PSO tuned PI regulator. Proceedings of the 2017 International Conference on Green Energy Conversion Systems (GECS), Hammamet, Tunisia.10.1109/GECS.2017.8066235 ↗
21. PSO based optimized fuzzy controllers for decoupled highly interacted distilla-tion process10.1016/j.asej.2012.03.002 ↗
22. The PID controller optimisation module using Fuzzy Self-Tuning PSO for Air Handling Unit in continuous operation10.1016/j.engappai.2022.105485 ↗
23. Mechanical properties test and finite element analysis for litchi
24. Dynamic observation on fruit growth and devel-opment of two litchi varieties
25. A review of PID control, tuning methods and applications10.1007/s40435-020-00665-4 ↗
26. Wang, H. (2014, January 26–27). Main steam temperature control system based on fuzzy control scheme. Proceedings of the 2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China.10.1109/IHMSC.2014.125 ↗
27. Lin, H., Cao, B., Liao, Y., Lin, H., Cao, B., and Liao, Y. (2018). Fuzzy Control. Fuzzy Sets Theory Preliminary: Can a Washing Machine Think?, Springer.10.1007/978-3-319-70749-5 ↗
28. Linearly decreasing inertia weight PSO and improved weight fac-tor-based clustering algorithm for wireless sensor networks10.1007/s12652-021-03534-w ↗
29. Silva, G.J., Datta, A., and Bhattachaiyya, S.P. (2005). PID Controllers for Time-Delay Systems, Springer.10.1007/b138796 ↗
30. Analysis of heat transfer characteristics of postitive fruits and vegetables under heat treatment conditions