Skip to main content

Adaptive Fuzzy Control of a Rotary Dryer

  • Chapter
Industrial Applications of Soft Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 71))

Abstract

Drying, especially rotary drying is without doubt one of the oldest and most usual unit operations in process industries. Rotary dryers are workhorses, the operation of which is easy and sure, but neither energy efficient nor environmentally friendly. To answer better to the requirements of the modern society concerning working conditions, safety practices and environmental aspects the sophisticated control offers the opportunity to improve dryer operation and efficiency.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Baker, C. G J (1983): Cascading rotary dryers. In: Proc. Drying’83, 2, 1–48

    Google Scholar 

  • Beck, M S, Bunn, P R, Gough, N E Wormald C N (1971): Computer control of a pilot scale rotary solids drier. In: Preprints 3rd IFACIIFIP Conference on Digital Computer Applications to Process Control, Helsinki, Part 2: XII-4, 1–7

    Google Scholar 

  • Cammarata, L., Yliniemi, L. (1999): Development of a self-tuning fuzzy logic controller for a rotary dryer. Report A No 10, Control Engineering Laboratory, University of Oulu.

    Google Scholar 

  • Chen, J.Y., Lin Y.H. (1997): A self-tuning fuzzy controller design. In: Proc. IEEE International Conference on Neural Networks 3, 1358–1362

    Chapter  Google Scholar 

  • Chiricozzi, E., Parasiliti, F., Ptursini, M., Mang D.O. (1995); Fuzzy self-tuning PI control of PM synchronous motor drives. In: Proc. International Conference on Power Electronics and Drive Systems 2, 749–754

    Google Scholar 

  • Chung, H.Y., Chen, B.C., Lin, C.C. (1998): A PI-type fuzzy controller with self-tuning scaling factors. Fuzzy Sets and Systems 93, 23–28

    Article  Google Scholar 

  • Daugherity, W.C., Rathakrishnan, B., Yen, Y. (1992): Performance evaluation of a self-tuning fuzzy controller. In: Proc. IEEE International Conference on Fuzzy Systems 389–397

    Google Scholar 

  • Douglas, P.L., Kwade, A., Lee P.L., Mallick, S.K., Whaley, M.G. (1992): Modelling, simulation and control of rotary sugar dryers. In: Proc. Drying’92, 1928–1933

    Google Scholar 

  • Duchesne, C., Thibault, J., Bazin, C. (1997): Dynamics and assessment of some control strategies of a simulated industrial rotary dryer. Drying Technology 15 (2), 477–510

    Article  Google Scholar 

  • Harbert, F.C. (1973): Control of dryers by the temperature difference technique. Instruments and Control Systems 46 (9), 71–72

    Google Scholar 

  • Harbert, F.C. (1974): Automatic control of drying processes: Moisture measurement and control by the temperature difference method. Chem. Eng. Sci. 29, b888–890

    Article  Google Scholar 

  • He, S.Z., Tan, S., Xu, F.L. (1993): Fuzzy self-tuning of PID controllers. Fuzzy Sets and Systems 56, 37–46

    Article  Google Scholar 

  • Jung, C.H., Ham, C.S. Lee, K.I. (1995): A real-time self-tuning fuzzy controller through scaling factor adjustment for the steam generator of NNP. Fuzzy Sets and Systems 7, 53–60

    Google Scholar 

  • Koskinen, J., Yliniemi, L., Leiviskä, K. (1998): Fuzzy modelling of a pilot plant rotary dryer. In: Proc. UKACC International Conference on CONTROL’98. Swansea, 1, 515–518

    Chapter  Google Scholar 

  • Koskinen, J. (1999): Rumpukuivaimen sumea mallintaminen. Lic.Thesis. University of Oulu, Department of Process Engineering

    Google Scholar 

  • Lui, H.C., Gun, M.K., Goh, T.H. Wang, P.Z. (1994): A self-tuning adaptive resolution (STAR) fuzzy control algorithms. In: Proc.3rd IEEE World Congress on Computational Intelligence. 3, 1508–1513

    Google Scholar 

  • Miyata, H., Ohki, M., Ohikita, M. (1996): Self-tuning of fuzzy reasoning by the steepest descent method and its application to a parallel parking. IEICE Transactions on Information and Systems e79-d (5), 561–569

    Google Scholar 

  • Mudi, R.K. Pal, N.R. (1998): A robust self-tuning scheme of PI-type and PD-type fuzzy controllers. IEEE transactions on Fuzzy Systems 7 (1), 2–16

    Google Scholar 

  • Perry, J.H. (1963): Chemical Engineers’ Handbook. McGraw–Hill Inc, New York, 22–122–107

    Google Scholar 

  • Pietranski, J.F., Marsolan, N.F. King K.-H. (1982): Expert fuzzy process control of a rotary dryer. In: Proc. American Control Conference, New York, 1359–1362

    Google Scholar 

  • Ramkumar, K.B., Chidambaram, M. (1995): Fuzzy self-tuning PI controller for bioreactors. Bioprocess Engineering 12 (5), 263–267

    Article  Google Scholar 

  • Robinson, J.W. (1989): The Delta T-A new drying model for pulp and paper. In: Proc. TAPPI Engineering Conference. Tappi Press, Atlanta, 183–187

    Google Scholar 

  • Robinson, J.W. (1992): Improve dryer control. Chem. Eng. Progress, December 28–33

    Google Scholar 

  • Shinskey, F.G. (1974): Process control systems with variable structure. Control Engineering, August 63–66

    Google Scholar 

  • Strumillo, C. Kudra, T. (1986): Drying: Principles, Applications and Design. Gordon and Breach Science Publishers, Montreaux

    Google Scholar 

  • Wright, D.J. (1976): Continuous moisture measurement in mining processes. In: Proc. Instrumentation in the Mining and Metallurgy Industries, Vancouver, 8–10

    Google Scholar 

  • Yliniemi, L., Koskinen, J., Leiviskä, K. (1998): Advanced control of a rotary dryer. In: Heidepriem, J. (ed.): Automation in Mining, Mineral and Metal Processing Preprints. Elsevier Science, NewYork, pp. 127–132

    Google Scholar 

  • Yliniemi, L. (1999): Advanced control of a rotary dryer. Dissertation, University of Oulu, Department of Process Engineering

    Google Scholar 

  • Zheng, J., Guo, P.,.Wang, J.D. (1992): STFC–self-tuning fuzzy controller. In: Proc. IEEE International Conference on Systems, Man and Cybernetics 2, 1603–1608

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Yliniemi, L. (2001). Adaptive Fuzzy Control of a Rotary Dryer. In: Leiviskä, K. (eds) Industrial Applications of Soft Computing. Studies in Fuzziness and Soft Computing, vol 71. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1822-2_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-7908-1822-2_8

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2488-9

  • Online ISBN: 978-3-7908-1822-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics