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Development of Fractional-Order Model Reference Adaptive Control of a Higher-Order Ball and Beam System with Actuator Dynamics


Authors : Salisu Umar; Nura Ahmed Muhammad

Volume/Issue : Volume 11 - 2026, Issue 8 - August


Google Scholar : https://tinyurl.com/mvtydasx

DOI : https://doi.org/10.38124/ijisrt/26aug846

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : This study develops a fractional-order model reference adaptive controller (FOMRAC) for a higher-order balland-beam system in which actuator behaviour is explicitly represented. The experimental platform comprises a 0.60 m beam, a 2.7 g ball with a 20 mm radius, a Hitec HS-645MG servo, an Arduino UNO controller, and a VL53L1 time-of-flight position sensor. The ball dynamics are obtained from the rolling constraint and then linearised about the horizontal equilibrium. Recalculation from the parameters gives an effective rolling mass of 7.02 × 10⁻³ kg and a nominal ballposition/beam-angle gain of −0.25154 s⁻². Actuator dynamics are retained in the higher-order representation rather than being treated as instantaneous. A Caputo fractional-order adaptation law is incorporated into a Lyapunov-based MRAC structure. PID, integer-order MRAC, and FOMRAC are compared using the performance measures, while four recorded laboratory PID trajectories are used to illustrate the sensitivity of the physical platform to gain selection. Under the model, FOMRAC gives a settling time of 1.880 s and the smallest IAE and ITAE among the three controllers. The results support the use of fractional adaptation as an additional tuning dimension for practical ball-and-beam control.

Keywords : FOMRAC; MRAC; PID; Ball-and-Beam; Actuator Dynamics; Arduino; VL53L1.

References :

  1. Aburakhis, M., & Ordóñez, R. (2024). Generalization of direct adaptive control using fractional calculus applied to nonlinear systems. Journal of Control, Automation and Electrical Systems, 35, 428–439. https://doi.org/10.1007/s40313-024-01082-0
  2. Ahmad, B., & Hussain, I. (2017). Design and hardware implementation of ball & beam setup. In Proceedings of the 5th International Conference on Aerospace Science and Engineering (ICASE 2017) (pp. 194–199). IEEE. https://doi.org/10.1109/ICASE.2017.8374271
  3. Arabi, E., Panagou, D., Yucelen, T., & Nguyen, N. T. (2020). Model reference adaptive control of uncertain dynamical systems subject to high-order actuator dynamics with performance guarantees. In AIAA Scitech 2020 Forum. https://doi.org/10.2514/6.2020-0591
  4. Gruenwald, B. C., Yucelen, T., Muse, J. A., & Wagner, D. (2019). Computing stability limits for adaptive control laws with high-order actuator dynamics. Automatica, 101, 409–416. https://doi.org/10.1016/j.automatica.2018.12.025
  5. Hitec Commercial Solutions. (2026). HS-645MG high torque metal gear servo: General specifications. https://www.hiteccs.com/actuators/product-details/HS-645MG
  6. Kao, Y., Wang, C., Xia, H., & Cao, Y. (2024). Analysis and control for fractional-order systems. Springer. https://doi.org/10.1007/978-981-99-6054-5
  7. Khan, R., Malik, F. M., Raza, A., Mazhar, N., Ullah, H., & Umair, M. (2020). Robust nonlinear control design and disturbance estimation for ball and beam system. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET 2020). IEEE. https://doi.org/10.1109/iCoMET48670.2020.9073936
  8. Monje, C. A., Chen, Y. Q., Vinagre, B. M., Xue, D., & Feliu-Batlle, V. (2010). Fractional-order systems and controls: Fundamentals and applications. Springer. https://doi.org/10.1007/978-1-84996-335-0
  9. Patel, V. V. (2020). Ziegler–Nichols tuning method: Understanding the PID controller. Resonance, 25(10), 1385–1397. https://doi.org/10.1007/s12045-020-1058-z
  10. Romdlony, M. Z., Rosa, M. R., Syamsudin, E. M. P., Trilaksono, B. R., & Wibowo, A. S. (2022). Design and application of models reference adaptive control (MRAC) on ball and beam. Journal of Mechatronics, Electrical Power, and Vehicular Technology, 13(1), 15–23. https://doi.org/10.14203/j.mev.2022.v13.15-23
  11. Sutera, G., Guastella, D. C., Cancelliere, F., & Muscato, G. (2026). Design and implementation of a ball and beam control system using a PID controller. IEEE Transactions on Education. https://doi.org/10.1109/TE.2026.3653647

This study develops a fractional-order model reference adaptive controller (FOMRAC) for a higher-order balland-beam system in which actuator behaviour is explicitly represented. The experimental platform comprises a 0.60 m beam, a 2.7 g ball with a 20 mm radius, a Hitec HS-645MG servo, an Arduino UNO controller, and a VL53L1 time-of-flight position sensor. The ball dynamics are obtained from the rolling constraint and then linearised about the horizontal equilibrium. Recalculation from the parameters gives an effective rolling mass of 7.02 × 10⁻³ kg and a nominal ballposition/beam-angle gain of −0.25154 s⁻². Actuator dynamics are retained in the higher-order representation rather than being treated as instantaneous. A Caputo fractional-order adaptation law is incorporated into a Lyapunov-based MRAC structure. PID, integer-order MRAC, and FOMRAC are compared using the performance measures, while four recorded laboratory PID trajectories are used to illustrate the sensitivity of the physical platform to gain selection. Under the model, FOMRAC gives a settling time of 1.880 s and the smallest IAE and ITAE among the three controllers. The results support the use of fractional adaptation as an additional tuning dimension for practical ball-and-beam control.

Keywords : FOMRAC; MRAC; PID; Ball-and-Beam; Actuator Dynamics; Arduino; VL53L1.

Paper Submission Last Date
30 - September - 2026

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