Skip to main content

Adaptive Neuro-Fuzzy-PID and Fuzzy-PID-Based Controller Design for Helicopter System

  • Conference paper
  • First Online:
Applications of Computing, Automation and Wireless Systems in Electrical Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 553))

Abstract

The paper presents designing and control of two-degree-of-freedom helicopter system, with two degrees of freedom. The helicopter is a combination of rotor motors which helps to lift the body of system. This is a nonlinear and unstable system in nature. The control techniques focused are adaptive neuro-fuzzy inference-PID and fuzzy-PID. Helicopter system has been analysed using MATLAB software and analysed in terms of transient response, root-mean-square error, steady-state error and total harmonic distortion analysis for performance assessment. The controllers have been designed with and without integral action.

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
Hardcover Book
USD 219.99
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

Similar content being viewed by others

References

  1. Chalupa P, Přikryl J, Novák J (2015) Modelling of twin rotor MIMO system. In: Proceedings 2015 20th international conference on process control. PC 2015, vol. 2015–July, pp. 314–319

    Google Scholar 

  2. Rotondo D, Nejjari F, Puig V (2013) Quasi-LPV modeling, identification and control of a twin rotor MIMO system. Control Eng Pract 21(6):829–846

    Article  Google Scholar 

  3. Tastemirov A, Lecchini-Visintini A, Morales-Viviescas RM (2017) Complete dynamic model of the twin rotor MIMO system (TRMS) with experimental validation. Control Eng Pract 66(July):89–98

    Article  Google Scholar 

  4. Paul PK, Jacob J (2017) On the modeling of twin rotor MIMO system using chirp inputs as test signals. Asian J Control 19(5):1731–1740

    MathSciNet  MATH  Google Scholar 

  5. Juang JG, Te Huang M, Liu WK (2008) PID control using presearched genetic algorithms for a MIMO system. IEEE Trans Syst Man Cybern Part C Appl Rev 38(5):716–727

    Google Scholar 

  6. Alagoz BB, Ates A, Yeroglu C (2013) Auto-tuning of PID controller according to fractional-order reference model approximation for DC rotor control. Mechatronics 23(7):789–797

    Article  Google Scholar 

  7. Tao CW, Taur JS, Chen YC (2010) Design of a parallel distributed fuzzy LQR controller for the twin rotor multi-input multi-output system. Fuzzy Sets Syst 161(15):2081–2103

    Article  MathSciNet  Google Scholar 

  8. Tao CW, Taur JS, Chang YH, Chang CW (2010) A novel fuzzy-sliding and fuzzy-integral-sliding controller for the twin-rotor multi-input multi-output system. IEEE Trans Fuzzy Syst 18(5):893–905

    Article  Google Scholar 

  9. Jahed M, Farrokhi M (2013) Robust adaptive fuzzy control of twin rotor MIMO system. Soft Comput 17(10):1847–1860

    Article  Google Scholar 

  10. Rahideh A, Bajodah AH, Shaheed MH (2012) Real time adaptive nonlinear model inversion control of a twin rotor MIMO system using neural networks. Eng Appl Artif Intell 25(6):1289–1297

    Article  Google Scholar 

  11. Shaik FA, Purwar S, Pratap B (2011) Real-time implementation of Chebyshev neural network observer for twin rotor control system. Expert Syst Appl 38(10):13043–13049

    Article  Google Scholar 

  12. Rahideh A, Hasan Shaheed M (2011) Stable model predictive control for a nonlinear system. J Franklin Inst 348(8):1983–2004

    Article  MathSciNet  Google Scholar 

  13. Rahideh A, Shaheed MH (2012) Constrained output feedback model predictive control for nonlinear systems. Control Eng. Pract 20(4):431–443

    Article  Google Scholar 

  14. Mondal S, Mahanta C (2012) Adaptive second-order sliding mode controller for a twin rotor multi-input–multi-output system. IET Control Theory Appl 6(14):2157–2167

    Article  MathSciNet  Google Scholar 

  15. Rashad R, El-Badawy A, Aboudonia A (2017) Sliding mode disturbance observer-based control of a twin rotor MIMO system. ISA Trans 69:166–174

    Article  Google Scholar 

  16. Yang X, Cui J, Lao D, Li D, Chen J (2014) Input shaping enhanced active disturbance rejection control for a twin rotor multi-input multi-output system (TRMS). ISA Trans 62:287–298

    Article  Google Scholar 

  17. Haruna A, Mohamed Z, Efe M, Basri MAM (2017) Dual boundary conditional integral backstepping control of a twin rotor MIMO system. J Franklin Inst 354(15):6831–6854

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rupam Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Singh, R., Bhushan, B. (2019). Adaptive Neuro-Fuzzy-PID and Fuzzy-PID-Based Controller Design for Helicopter System. In: Mishra, S., Sood, Y., Tomar, A. (eds) Applications of Computing, Automation and Wireless Systems in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-13-6772-4_25

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-6772-4_25

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6771-7

  • Online ISBN: 978-981-13-6772-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics