Skip to main content

Optimal Tuning of PID Controller for Centrifugal Temperature Control System in Sugar Industry Using Genetic Algorithm

  • Conference paper
  • First Online:
Proceedings of Fifth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 437))

  • 1336 Accesses

Abstract

This paper presents optimal tuning of the PID controllers for regulating the temperature in a heat exchanger of centrifugal machines in sugar industry using genetic algorithm. For filtering out sugar from the molasses centrifugal machines are operated at certain temperature and any alterations from the set point will drastically affect the process safety and product quality. The PID controller maintains the temperature of the outgoing fluid at a desired level and that too in a short duration of time, and must be able to adapt to the external disturbances and accept the new set points dynamically. Initially, an oscillatory behavior has been obtained for the PID controller tuned using RTR, followed by optimization using genetic algorithms. The GA optimized PID controller shows better response irrespective of the conventional RTR tuned PID in terms of the performance indices.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Åström, K.J., Hägglund, T.: The future of PID control. Control Eng. Practice, 1163–1175 (2001)

    Google Scholar 

  2. Zhao, S.Z., Iruthayarajan, M.W., Baskar, S., Suganthan, P.N.: Multi-objective robust PID controller tuning using two lbests multiobjective particle swarm optimization. Inf. Sci. 181(16), 3323–3335 (2011)

    Article  Google Scholar 

  3. Krohling, R.A.., Rey, J.P.: Design of optimal disturbance rejection PID controllers using genetic algorithms. Evolutionary Computation, IEEE Transactions on 5(1), 78–82 (2001)

    Article  Google Scholar 

  4. Stephanopoulos, G., Reklaitis, G.V.: Process systems engineering: From Solvay to modern bio-and nanotechnology.: A history of development, successes and prospects for the future. Chem. Eng. Sci. 66(19), 4272–4306 (2011)

    Article  Google Scholar 

  5. Nikacevic, N.M., Huesman, A.E., Van den Hof, P.M., Stankiewicz, A.I.: Opportunities and challenges for process control in process intensification. In: Chemical Engineering and Processing: Process Intensification (2011)

    Google Scholar 

  6. Optimization Toolbox-Matlab

    Google Scholar 

  7. Singh, S.K., Boolchandani, D., Modani, S.G., Katal, N.: Multi-objective optimization of PID controller for temperature control in centrifugal machines using genetic algorithm. Res. J. Appl. Sci., Eng. Technol. 7(9), 1794–1802 (2014)

    Google Scholar 

  8. Nise, N.S.: Control System Engineering, 4th edn. (2003)

    Google Scholar 

  9. Larbes, C., Aït Cheikh, S.M., Obeidi, T., Zerguerras, A.: Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system. Renewable Energy, Elsevier Ltd. 34(10), 2093–2100 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sanjay Kumar Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this paper

Cite this paper

Singh, S.K., Boolchandani, D., Modani, S.G., Katal, N. (2016). Optimal Tuning of PID Controller for Centrifugal Temperature Control System in Sugar Industry Using Genetic Algorithm. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-10-0451-3_18

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-0451-3_18

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0450-6

  • Online ISBN: 978-981-10-0451-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics