Skip to main content

PID Controller Based on Flower Pollination Algorithm of Flexible Beam System

  • Conference paper
  • First Online:
Recent Trends in Mechatronics Towards Industry 4.0

Abstract

Flexible beam is commonly used in a wide variety of engineering applications such as mechanical, aircraft and architecture. One of the advantages of these flexible structures is its lighter as compared to rigid structures. However, flexible structures are more sensitive to vibration compared to rigid structures. Excessive long term vibration can damage parts and reduce the performance of such structures. Therefore, a suitable system should be identified to overcome the problem. In the new era of technology, there are many methods developed to suppress unwanted vibration. One well-known system to suppress unwanted vibration is active vibration control (AVC). This system is suitable for structures experiencing low frequency of vibration. A proper modelling must be developed using system identification techniques in order to achieve high vibration cancellation in the system. For system identification, evolutionary swarm algorithm is the latest technique used compared to other methods. In this study, flower pollination algorithms (FPA) was used to develop a mathematical model of a system. The main objective of this study was to develop a model for flexible beam system using FPA in order to achieve an approximate model that represents the real characteristic of the flexible beam system. The developed model will then be used as a platform for PID controller development. The model was validated using three robustness methods, which are the mean squared error (MSE), correlation test, and pole zero diagram stability. Based on the validation, it was observed that the FPA was able to exhibit the lowest MSE value, very good correlation test and high stability. The model achieved in this study was used in controller development for vibration cancellation of a flexible beam system. It was noticed that the PID controller achieved 17.7 dB of attenuation level at the first mode of vibration. The attenuation of vibration was reduced from 56.72 to 39.03 dB, which is equivalent to 31.2% of reduction when the vibration control is active.

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 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
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

References

  1. Zhang D, Jia J, Guo Y, Duan Y (2006) Research on active and passive compound vibration control based on photoelectric displacement detection. In: 6th World congress on intelligent control and automation. IEEE, Dalian, China

    Google Scholar 

  2. Rahman TAZ, Darus IZM (2011) Active vibration control of a flexible plate via active force control strategy. In: 4th International conference on mechatronics (ICOM). IEEE, Kuala Lumpur

    Google Scholar 

  3. Hadi MS, Darus IZM, Tokhi MO, Jamid MF (2019) Active vibration control of a horizontal flexible plate structure using intelligent proportional–integral–derivative controller tuned by fuzzy logic and artificial bee colony. J Low Freq Noise Vibr Active Control 0(0):1–13

    Google Scholar 

  4. Hadi MS, Darus IZM, Yatim HM, Talib MHA, Jamali A (2019) Fuzzy-PID based controller for active vibration control of nonlinear dynamic systems. In: 22nd International conference on climbing and walking robots and the support technologies for mobile machines. CLAWAR Association Ltd, Kuala Lumpur, Malaysia

    Google Scholar 

  5. Fu L, Li P (2013) The research survey of system identification method. In: 5th International conference on intelligent human-machine systems and cybernetics. IEEE, Hangzhou, China

    Google Scholar 

  6. Quan H, Shi X (2009) Evolutionary swarm algorithm based on evolutionary swarm model. In: WRI global congress on intelligent systems. IEEE, Xiamen, China

    Google Scholar 

  7. Bonabeau E, Dorigo M, Theraulaz G (2001) Swarm intelligence: from natural to artificial systems. Q Rev Biol 76(2):268–269

    MATH  Google Scholar 

  8. Wahab MNA, Nefti-Meziani S, Atyabi A (2015) A comprehensive review of swarm optimization algorithms. Plos One 10(5)

    Google Scholar 

  9. Eek RTP, Darus IZM, Sahlan S, Samin PM, Shaharuddin NMR (2016) Implementation of swarm algorithm in modeling a flexible beam structure. J VibroEng 18(8):4914–4934

    Article  Google Scholar 

  10. Nabil E (2016) A modified flower pollination algorithm for global optimization. Expert Syst Appl 57:192–203

    Article  Google Scholar 

  11. Yang XS (2012) Flower pollination algorithm for global optimization. In: Unconventional computation and natural computation lecture notes in computer science, pp 240–249

    Google Scholar 

  12. Glover BJ (2014) Understanding flowers and flowering. Oxford University Press, Oxford

    Book  Google Scholar 

  13. Singh S, Ashok A, Rawat TK, Kumar M (2016) Optimal IIR system identification using flower pollination algorithm. In: 1st International conference on power electronics, intelligent control and energy systems (ICPEICES), IEEE, Delhi, India

    Google Scholar 

  14. Chiroma H, Shuib NLM, Muaz SA, Abubakar AI, Ila LB, Maitama JZ (2015) A review of the applications of bio-inspired flower pollination algorithm. Procedia Comput Sci 62:435–441

    Article  Google Scholar 

  15. He X, Yang XS, Karamanoglu M, Zhao Y (2017) Global convergence analysis of the flower pollination algorithm: a discrete-time Markov chain approach. Procedia Comput Sci 108:1354–1363

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to Universiti Teknologi MARA (UiTM), Universiti Teknologi Malaysia (UTM) and Ministry of Higher Education (MoHE) for funding the research and providing facilities to conduct this research. Sponsor file number (RACER/1/2019/TK03/UITM//1).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhamad Sukri Hadi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Fadzli, A.A.M., Hadi, M.S., Eek, R.T.P., Talib, M.H.A., Yatim, H.M., Darus, I.Z.M. (2022). PID Controller Based on Flower Pollination Algorithm of Flexible Beam System. In: Ab. Nasir, A.F., Ibrahim, A.N., Ishak, I., Mat Yahya, N., Zakaria, M.A., P. P. Abdul Majeed, A. (eds) Recent Trends in Mechatronics Towards Industry 4.0. Lecture Notes in Electrical Engineering, vol 730. Springer, Singapore. https://doi.org/10.1007/978-981-33-4597-3_17

Download citation

Publish with us

Policies and ethics