InECCE2019 pp 47-58 | Cite as

A Fictitious Reference Iterative Tuning Method for Buck Converter-Powered DC Motor Control System

  • Mohd Syakirin RamliEmail author
  • Seet Meng Sian
  • Mohd Naharudin Salim
  • Hamzah Ahmad
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 632)


This paper presents a model-free optimization algorithm for a PID controller based on Fictitious Reference Iterative Tuning and Simulated Kalman Filter. The modeling of a buck converted-powered DC motor system is first provided to form the basis of data collection and fictitious reference signal derivation. The supplied model is however not a necessity in the scope of this work but is provided for the purpose of performance comparison. A cost function is formulated based on the minimization of error between the output response of the desired model with the output response of the closed-loop system. Simulation analyses using Matlab Software have been conducted for results validation and verification. Furthermore, a performance comparison between the proposed method and a model-based controller design has been carried out. From the numerical example, it shows that the system with the tuned PID controller exhibited a better angular velocity trajectory tracking compared to the system with the state feedback controller with integral gain.


Fictitious reference Model-free Simulated Kalman filter Controller tuning PID control 



Special thanks and appreciation belong to Universiti Malaysia Pahang for providing financial assistance towards completing this research work. This paper has been supported under the short-term grant of RDU1703139.


  1. 1.
    Parasiliti F, Villani M, Castello M (2014) PM brushless DC motor with exterior rotor for high-efficiency household appliances. In: 2014 international conference on electrical machines, ICEM 2014, pp 623–628Google Scholar
  2. 2.
    Hwang CC, Liu PL, Li CT, Chen C (2012) Design and analysis of a brushless DC motor for applications in robotics. IET Electr Power Appl 6(7):385–389CrossRefGoogle Scholar
  3. 3.
    Rajesh D, Ravikumar D, Bharadwaj SK, Vastav BKS (2016) Design and control of digital DC drives in steel rolling mills. Int Conf Inven Comput Technol, ICICT 2016:1–5Google Scholar
  4. 4.
    Hall RD, Konstanty WJ (2010) Commutation of DC motors. IEEE Ind Appl Mag (16):56–62Google Scholar
  5. 5.
    Silva-Ortigoza R, Hernández-Guzmán VM, Antonio-Cruz M, Muñoz-Carrillo D (2015) DC/DC buck power converter as a smooth starter for a DC motor based on a hierarchical control. IEEE Trans Power Electron 30(2):1076–1084CrossRefGoogle Scholar
  6. 6.
    Beevi A, Noufal M (2016) Hierarchical control For a buck converter driven DC motor. Int J Adv Res Electr, Electron Instrum Eng 5(9):7218–7224Google Scholar
  7. 7.
    Hernandez-Marquez E, Silva-Ortigoza R, Dong SH, Garcia-Rodriguez VH, Saldana-Gonzalez G, Marcelino-Aranda M (2016) A new DC/DC buck-boost converter-DC motor system: modeling and simulation. Int Conf MechatronS, Electron, Automot Eng, ICMEAE 2016:101–106Google Scholar
  8. 8.
    Ahmad MA, Raja Ismail RMT, Ramli MS (2010) Control strategy of buck converter driven DC motor: a comparative assessment. Aust J Basic Appl Sci (10):4893–4903Google Scholar
  9. 9.
    Linares-Flores J, Sira-Ramírez H (2017) Sliding mode-delta modulation GPI control of a DC motor through a buck converter. IFAC Proc Vol 37(21):405–410CrossRefGoogle Scholar
  10. 10.
    Kamarposhti MA, Tayebbifar T, Shaker M, Nouri P (2013) The control of buck-boost DC-DC converters for DC motor drives on variable DC voltage by using neural network. Life Sci J 10(5):236–240Google Scholar
  11. 11.
    Ahmad MA, Raja Ismail, RMT (2017) A data-driven sigmoid-based PI controller for buck-converter powered DC motor. In: IEEE symposium on computer applications and industrial electronics, pp 81–86Google Scholar
  12. 12.
    Li G, Liu L (2012) Robust adaptive coordinated attitude control problem with unknown communication delays and uncertainties. Procedia Eng 29:1447–1455CrossRefGoogle Scholar
  13. 13.
    Battistelli G, Selvi D, Mari D, Tesi P (2014) Unfalsified approach to data-driven control design. In: IEEE conference on decision and control, pp 6003–6008Google Scholar
  14. 14.
    Saleem O, Rizwan M (2019) Performance optimization of LQR-based PID controller for DC-DC buck converter via iterative-learning-tuning of state-weighting matrix. Int J Numer Model: Electron Netw, Devices Fields, 1–17Google Scholar
  15. 15.
    Rallo G, Formentin S, Rojas CR, Savaresi SM (2018) Experiment design for virtual reference feedback tuning. In: IEEE conference on decision and control, pp 2271–2276Google Scholar
  16. 16.
    Kaneko O, Soma S, Fujii T (2005) A fictitious reference iterative tuning (FRIT) in the two degrees of freedom control scheme and its application to closed-loop system identification. IFAC Proc Vol 626–631Google Scholar
  17. 17.
    Nguyen HT, Kaneko O, Yamamoto S (2011) Data-driven IMC for non-minimum phase systems—Laguerre expansion approach. In: 50th IEEE conference on decision and control and european control conference, pp 476–481Google Scholar
  18. 18.
    Ramli MS, Ahmad H (2018) Data-driven impedance matching in multilateral teleoperation systems. Indones J Electr Eng Comput Sci 10(2):713–724CrossRefGoogle Scholar
  19. 19.
    Hou ZS, Wang Z (2013) From model-based control to data-driven control: survey, classification and perspective. Inf Sci 235:3–35MathSciNetCrossRefGoogle Scholar
  20. 20.
    Ibrahim Z et al (2015) A Kalman filter approach for solving unimodal optimization problems. ICIC Express Lett 9(12):3415–3422Google Scholar
  21. 21.
    Ibrahim Z, Abdul Aziz NH, Nor NA, Razali S, Mohamad MS (2016) Simulated Kalman filter: a novel estimation-based metaheuristic optimization algorithm. Adv Sci Lett 22(10):2941–2946CrossRefGoogle Scholar
  22. 22.
    Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82:35–45MathSciNetCrossRefGoogle Scholar
  23. 23.
    Ramli MS, Rahmat MF (2008) Servomotor control using direct digital control and state space technique. J Teknologi 49(D):45–60Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Mohd Syakirin Ramli
    • 1
    Email author
  • Seet Meng Sian
    • 1
  • Mohd Naharudin Salim
    • 1
  • Hamzah Ahmad
    • 1
  1. 1.Faculty of Electrical & Electronics EngineeringUniversiti Malaysia PahangPekanMalaysia

Personalised recommendations