Skip to main content

PID Controller for 2-DOFs Twin Rotor MIMO System Tuned with Particle Swarm Optimization

  • Conference paper
  • First Online:
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 (AISI 2019)

Abstract

This paper presents the modelling and control of a 2-DOFs Twin rotor multi input multi output (MIMO) system which is a laboratory setup resembling the dynamics of a helicopter. In this paper, the system modelling process is done using the common conventional mathematical model based on Euler-Lagrange method. The transfer functions of the model are used in the different tuning methods to reach the optimal PID gain values. The study uses conventional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers to obtain a robust controller for the system. Particle Swarm optimization (PSO) technique was used to tune the controller parameters. A state space model is obtained considering some design assumptions and simplifications. Statistical measurement and convergence analysis is evaluated for the optimization of gain parameters of the PID controller for 2-DOF Twin rotor system using PSO by iteratively minimizing integral of squared error (ISE) and integral of time multiplied by the squared error (ITSE). The results are verified through simulations and experiments.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Ammar, H.H., Azar, A.T., Tembi, T.D., Tony, K., Sosa, A.: Design and implementation of fuzzy pid controller into multi agent smart library system prototype. In: Hassanien, A.E., Tolba, M.F., Elhoseny, M., Mostafa, M. (eds.) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2018), pp. 127–137. Springer, Cham (2018)

    Chapter  Google Scholar 

  2. Azar, A.T., Serrano, F.E.: Robust IMC-PID tuning for cascade control systems with gain and phase margin specifications. Neural Comput. Appl. 25(5), 983–995 (2014)

    Article  Google Scholar 

  3. Azar, A.T., Serrano, F.E.: Adaptive Sliding Mode Control of the Furuta Pendulum, vol. 576, pp. 1–42. Springer, Cham (2015)

    Google Scholar 

  4. Azar, A.T., Ammar, H.H., Barakat, M.H., Saleh, M.A., Abdelwahed, M.A.: Self-balancing robot modeling and control using two degree of freedom PID controller. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 64–76. Springer, Cham (2019)

    Google Scholar 

  5. Azar, A.T., Hassan, H., Razali, M.S.A.B., de Brito Silva, G., Ali, H.R.: Two-degree of freedom proportional integral derivative (2-DOF PID) controller for robotic infusion stand. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 13–25. Springer, Cham (2019)

    Google Scholar 

  6. Cajo, R., Agila, W.: Evaluation of algorithms for linear and nonlinear PID control for twin rotor mimo system. In: 2015 Asia-Pacific Conference on Computer Aided System Engineering, pp. 214–219 (2015)

    Google Scholar 

  7. Chalupa, P., Přikryl, J., Novák, J.: Modelling of twin rotor mimo system. Procedia Eng. 100, 249–258 (2015). 25th DAAAM International Symposium on Intelligent Manufacturing and Automation (2014)

    Google Scholar 

  8. Chi, N.V.: Adaptive feedback linearization control for twin rotor multiple-input multiple-output system. Int. J. Control Autom. Syst. 15(3), 1267–1274 (2017)

    Article  Google Scholar 

  9. Chien, K., Hrones, J., Reswick, J.: On the automatic control of generalized passive systems. Trans. ASME 74(2), 175–185 (1952)

    Google Scholar 

  10. Dheeraj, K., Jacob, J., Nandakumar, M.P.: Direct adaptive neural control design for a class of nonlinear multi input multi output systems. IEEE Access 7(15), 424–15, 435 (2019)

    Google Scholar 

  11. Gorripotu, T.S., Samalla, H., Jagan Mohana Rao, C., Azar, A.T., Pelusi, D.: Tlbo algorithm optimized fractional-order PID controller for AGC of interconnected power system. In: Nayak, J., Abraham, A., Krishna, B.M., Chandra Sekhar, G.T., Das, A.K. (eds.) Soft Computing in Data Analytics, pp. 847–855. Springer, Singapore (2019)

    Chapter  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  14. Juang, J.G., Liu, W.K., Lin, R.W.: A hybrid intelligent controller for a twin rotor mimo system and its hardware implementation. ISA Trans. 50(4), 609–619 (2011)

    Article  Google Scholar 

  15. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995 - International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)

    Google Scholar 

  16. Messaoud, R.B.: Observer for nonlinear systems using mean value theorem and particle swarm optimization algorithm. ISA Trans. 85, 226–236 (2019)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  18. Pandey, V.K., Kar, I., Mahanta, C.: Control of twin-rotor mimo system using multiple models with second level adaptation. IFAC-PapersOnLine 49(1), 676–681 (2016). 4th IFAC Conference on Advances in Control and Optimization of Dynamical Systems ACODS 2016

    Google Scholar 

  19. Raghavan, R., Thomas, S.: Mimo model predictive controller design for a twin rotor aerodynamic system. In: 2016 IEEE International Conference on Industrial Technology (ICIT), pp. 96–100 (2016)

    Google Scholar 

  20. Raghavan, R., Thomas, S.: Practically implementable model predictive controller for a twin rotor multi-input multi-output system. J. Control Autom. Electrical Syst. 28(3), 358–370 (2017)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  23. Reynoso Meza, G., Blasco Ferragud, X., Sanchis Saez, J., Herrero Durá, J.M.: Multiobjective Optimization Design Procedure for Controller Tuning of a TRMS Process, pp. 201–213. Springer, Cham (2017)

    MATH  Google Scholar 

  24. Sodhi, P., Kar, I.: Adaptive backstepping control for a twin rotor mimo system. IFAC Proc. 47(1), 740–747 (2014). 3rd International Conference on Advances in Control and Optimization of Dynamical Systems (2014)

    Google Scholar 

  25. Tao, C., Taur, J., Chang, Y., Chang, C.: 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 (2010)

    Article  Google Scholar 

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

    Article  Google Scholar 

  27. Tiwalkar, R.G., Vanamane, S.S., Karvekar, S.S., Velhal, S.B.: Model predictive controller for position control of twin rotor mimo system. In: 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), pp. 952–957 (2017)

    Google Scholar 

  28. Wang, F.S., Juang, W.S., Chan, C.T.: Optimal tuning of PID controllers for single and cascade control loops. Chem. Eng. Commun. 132(1), 15–34 (1995)

    Article  Google Scholar 

  29. Ziegler, J., Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME 64(8), 759–768 (1942)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmad Taher Azar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Azar, A.T., Sayed, A.S., Shahin, A.S., Elkholy, H.A., Ammar, H.H. (2020). PID Controller for 2-DOFs Twin Rotor MIMO System Tuned with Particle Swarm Optimization. In: Hassanien, A., Shaalan, K., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. AISI 2019. Advances in Intelligent Systems and Computing, vol 1058. Springer, Cham. https://doi.org/10.1007/978-3-030-31129-2_22

Download citation

Publish with us

Policies and ethics