Publication Cover
Drying Technology
An International Journal
Volume 41, 2023 - Issue 7
269
Views
4
CrossRef citations to date
0
Altmetric
Research Articles

Predictive control of microwave hot-air coupled drying model based on GWO-BP neural network

ORCID Icon, ORCID Icon, ORCID Icon, , , & ORCID Icon show all
Pages 1148-1158 | Received 18 Jul 2022, Accepted 09 Sep 2022, Published online: 22 Sep 2022

References

  • Maftoonazad, N.; Dehghani, M. R.; Ramaswamy, H. S. Hybrid Microwave-Hot Air Tunnel Drying of Onion Slices: Drying Kinetics, Energy Efficiency, Product Rehydration, Color, and Flavor Characteristics. Drying Technol. 2022, 40, 966–986. DOI: 10.1080/07373937.2020.1841790.
  • Sabzevari, M.; Behroozi-Khazaei, N.; Darvishi, H. Real-Time Evaluation of Artificial Neural Network-Developed Model of Banana Slice Kinetics in Microwave-Hot Air Dryer. J. Food Process Eng. 2021, 44, e13796. DOI: 10.1111/jfpe.13796.
  • Sharma, N.; Singh, K. Model Predictive Control and Neural Network Predictive Control of TAME Reactive Distillation Column. Chem. Eng. Process. 2012a, 59, 9–21. DOI: 10.1016/j.cep.2012.05.003.
  • Li, F.; Qiao, J.; Han, H.; Yang, C. A Self-Organizing Cascade Neural Network with Random Weights for Nonlinear System Modeling. Appl. Soft Comput. 2016, 42, 184–193. DOI: 10.1016/j.asoc.2016.01.028.
  • Qiao, J.; Wang, L.; Yang, C. Adaptive Lasso Echo State Network Based on Modified Bayesian Information Criterion for Nonlinear System Modeling. Neural. Comput. Appl. 2019, 31, 6163–6177. DOI: 10.1007/s00521-018-3420-6.
  • Liu, J.; Huang, Y. L. Nonlinear Network Traffic Prediction Based on BP Neural Network. J. Comput. Appl. 2007, 27, 1770–1772.
  • Gillespie, M. T.; Best, C. M.; Townsend, E. C.; Wingate, D.; Killpack, M. D. 2018 Learning Nonlinear Dynamic Models of Soft Robots for Model Predictive Control with Neural Networks. 2018 IEEE International Conference on Soft Robotics (RoboSoft). 39–45. DOI: 10.1109/ROBOSOFT.2018.8404894.
  • Tian, Z.; Li, S.; Wang, Y. TS Fuzzy Neural Network Predictive Control for Burning Zone Temperature in Rotary Kiln with Improved Hierarchical Genetic Algorithm. Int. J. Model. Identif. Control. 2016, 25, 323–334. DOI: 10.1504/IJMIC.2016.076825.
  • Lin, Y. C.; Chen, D. D.; Chen, M.-S.; Chen, X.-M.; Li, J. A Precise BP Neural Network-Based Online Model Predictive Control Strategy for Die Forging Hydraulic Press Machine. Neural Comput. Appl. 2018, 29, 585–596. DOI: 10.1007/s00521-016-2556-5.
  • Mirjalili, S.; Mirjalili, S. M.; Lewis, A. Grey Wolf Optimizer. Adv. Eng. Softw. 2014, 69, 46–61. DOI: 10.1016/j.advengsoft.2013.12.007.
  • Mirjalili, S. How Effective is the Grey Wolf Optimizer in Training Multi-Layer Perceptrons. Appl. Intell. 2015, 43, 150–161. DOI: 10.1007/s10489-014-0645-7.
  • Katić, K.; Li, R.; Verhaart, J.; Zeiler, W. Neural Network Based Predictive Control of Personalized Heating Systems. Energy Build. 2018, 174, 199–213. DOI: 10.1016/j.enbuild.2018.06.033.
  • Chen, S.; Billings, S. A.; Grant, P. M. Non-Linear System Identification Using Neural Networks. Int. J. Control. 1990, 51, 1191–1214. DOI: 10.1080/00207179008934126.
  • Qian, K. A Temperature Predictive Control Method Using BP Neural Network. IOP Conf. Ser. Mater. Sci. Eng. 2020, 782, 032040. DOI: 10.1088/1757-899X/782/3/032040/meta.
  • Sahin, I.; Koyuncu, I. Design and Implementation of Neural Networks Neurons with RadBas, LogSig, and TanSig Activation Functions on FPGA. Elektronika Ir Elektrotech. 2012, 120, 51–54. DOI: 10.5755/j01.eee.120.4.1452.
  • Raeihagh, H.; Behbahaninia, A.; Aleagha, M. M. Risk Assessment of Sour Gas Inter-Phase Onshore Pipeline Using ANN and Fuzzy Inference System–Case Study: The South Pars Gas Field. J. Loss Prev. Process Ind. 2020, 68, 104238. DOI: 10.1016/j.jlp.2020.104238.
  • Nazareth, J. L. Conjugate Gradient Method. WIREs Comp Stat. 2009, 1, 348–353. DOI: 10.1002/wics.13.
  • Meza, J. C. Steepest Descent. WIREs Comp Stat. 2010, 2, 719–722. DOI: 10.1002/wics.117.
  • More, J. J.; Sorensen, D. C. Newton’s Method. (No. ANL-82-8). Argonne National Lab., IL (USA). DOI: 10.2172/5326201.
  • Su, M.; Xu, H. Remarks on the Gradient-Projection Algorithm. J Nonlin Anal Optim Theor Appl. 2010, 1, 35–43.
  • Benesty, J.; Chen, J.; Huang, Y.; Cohen, I. Pearson Correlation Coefficient. In Noise Reduction in Speech Processing. Springer, Berlin, Heidelberg. 2009, pp. 1–4. DOI: 10.1007/978-3-642-00296-0_5.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.