Digital Shadow-based Control of Temperature and Fault Classification in Shell and Tube Heat Exchanger using Fuzzy Logic Technique

Authors

  • Surendran T. Jeyarajah Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu 603203, India https://orcid.org/0009-0006-8922-2401
  • G. Joselin Retna Kumar Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu 603203, India
Volume: 14 | Issue: 3 | Pages: 14155-14161 | June 2024 | https://doi.org/10.48084/etasr.7061

Abstract

In this study, the Digital Shadow (DS) of the Shell and Tube Heat Exchanger (STHE) is designed and analyzed for numerous disturbances that occur when the system is in a running condition. The disruptive segregation of the heat exchanger is related to the DS for its operation, and thus a realistic DS was developed for the STHE. Fuzzy Logic (FL) was used to identify and segregate the disturbance signals from the process output. The Response Optimization (RO) algorithm was adopted and modified to work on the STHE. The observer-based residual generator design was implemented to prevent system failure and defective conditions. Model Predictive Controller (MPC), Transposed System Controller (TSC), and a looping-based control technique called Unity Response Loop (URL) were also implemented, and the results are discussed. The findings of this study contribute to the improvement of the overall performance of non-linear systems in industrial processes and the avoidance of defects.

Keywords:

controller design, digital shadow, fuzzy logic, heat transfer

Downloads

Download data is not yet available.

References

S. M. E. Sepasgozar, "Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment," Buildings, vol. 11, no. 4, Apr. 2021, Art. no. 151.

N. A. Khan, M. Sulaiman, P. Kumam, and M. A. Bakar, "Thermal Analysis of Conductive-Convective-Radiative Heat Exchangers With Temperature Dependent Thermal Conductivity," IEEE Access, vol. 9, pp. 138876–138902, 2021.

A. Noshadi, J. Shi, W. S. Lee, P. Shi, and A. Kalam, "Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system," Neural Computing and Applications, vol. 27, no. 7, pp. 2031–2046, Oct. 2016.

A. Guerra de Araujo Cruz, R. Delgado Gomes, F. Antonio Belo, and A. Cavalcante Lima Filho, "A Hybrid System Based on Fuzzy Logic to Failure Diagnosis in Induction Motors," IEEE Latin America Transactions, vol. 15, no. 8, pp. 1480–1489, 2017.

T. Surendran, K. Nandini, R. Nagalakshmi, and J. Johnsi, "Design Materials for Unity Control Loop," IOP Conference Series: Materials Science and Engineering, vol. 993, no. 1, Sep. 2020, Art. no. 012089.

A. Rasheed, O. San, and T. Kvamsdal, "Digital Twin: Values, Challenges and Enablers From a Modeling Perspective," IEEE Access, vol. 8, pp. 21980–22012, 2020.

A. Ladj, Z. Wang, O. Meski, F. Belkadi, M. Ritou, and C. Da Cunha, "A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective," Journal of Manufacturing Systems, vol. 58, pp. 168–179, Jan. 2021.

M. S. S. Asadi, H. Afarideh, M. Ghergherechi, and J. S. Chai, "Model Predictive Control-Based Smart Linear Servo-Motor Driver for a Resonance Frequency Tuner of Azimuth Variable Field Cyclotrons," Journal of the Korean Physical Society, vol. 76, no. 7, pp. 592–594, Apr. 2020.

L. Dong, L. Dou, J. Chen, and Y. Xia, "Hybrid model predictive control for speed control of permanent magnet synchronous motor with saturation," Journal of Control Theory and Applications, vol. 9, no. 2, pp. 251–255, May 2011.

K. H. Cho, Y. K. Yeo, J. S. Kim, and S. Koh, "Fuzzy model predictive control of nonlinear pH process," Korean Journal of Chemical Engineering, vol. 16, no. 2, pp. 208–214, Mar. 1999.

H. Wang, Y. Kang, L. Yao, H. Wang, and Z. Gao, "Fault Diagnosis and Fault Tolerant Control for T–S Fuzzy Stochastic Distribution Systems Subject to Sensor and Actuator Faults," IEEE Transactions on Fuzzy Systems, vol. 29, no. 11, pp. 3561–3569, Aug. 2021.

E. A. Esleman, G. Önal, and M. Kalyoncu, "Optimal PID and fuzzy logic based position controller design of an overhead crane using the Bees Algorithm," SN Applied Sciences, vol. 3, no. 10, Sep. 2021, Art. no. 811.

X. Weng, J. Zhang, and Y. Ma, "Path Following Control of Automated Guided Vehicle Based on Model Predictive Control with State Classification Model and Smooth Transition Strategy," International Journal of Automotive Technology, vol. 22, no. 3, pp. 677–686, Jun. 2021.

B. Pyun, M. Seo, S. Kim, and H. Choi, "Development of an Autonomous Driving Controller for Articulated Bus Using Model Predictive Control Algorithm with Inner Model," International Journal of Automotive Technology, vol. 23, no. 2, pp. 357–366, Apr. 2022.

A. A. Kapse, V. C. Shewale, S. D. Barahate, A. B. Kakade, and S. J. Surywanshi, "Experimental Investigation of Heat Transfer and Pressure Drop Performance of a Circular Tube with Coiled Wire Inserts," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12512–12517, Feb. 2024.

H. V. Nguyen, F. Deng, and T. D. Nguyen, "Optimal FLC-Sugeno Controller based on PSO for an Active Damping System," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12769–12774, Feb. 2024.

S. Barhate, R. Mudhalwadkar, and S. Madhe, "Fault Detection Methods Suitable for Automotive Applications in Proton Exchange Fuel Cells," Engineering, Technology & Applied Science Research, vol. 12, no. 6, pp. 9607–9613, Dec. 2022.

Downloads

How to Cite

[1]
S. T. Jeyarajah and G. J. R. Kumar, “Digital Shadow-based Control of Temperature and Fault Classification in Shell and Tube Heat Exchanger using Fuzzy Logic Technique”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 3, pp. 14155–14161, Jun. 2024.

Metrics

Abstract Views: 160
PDF Downloads: 122

Metrics Information