Online Identification of Differential Robots Using Relay Techniques
DOI:
https://doi.org/10.17979/ja-cea.2025.46.12189Keywords:
Mobile robots, Identification for control, Adaptive controlAbstract
This work presents an online identification and auto-tuning strategy based on symmetric relay feedback with hysteresis for estimating the dynamic velocity model of mobile robots. This method enables accurate system model estimation in the presence of load variations, while reducing both the disturbance to the system and the need for prior knowledge of its dynamics. The implementation was carried out on the Khepera IV robot and experimentally validated in three different cases: suspended, in its nominal configuration, and with additional load. The results show that, in less than 0,3 s, it is possible to obtain parameters for accurate first- and second-order dynamic models with delay. SIMC (Simple Internal Model Control) tuning rules are applied to these models for automatic PID controller adjustment. The closed-loop results demonstrate a significant improvement in the controller’s response, with a stable time constant despite load variations.
References
Ayyad, A., Chehadeh, M., Awad, M. I., Zweiri, Y., 2020. Real-time system identification using deep learning for linear processes with application to unmanned aerial vehicles. IEEE Access 8, 122539–122553.
Draganjac, I., Miklic, D., Kovacic, Z., Vasiljevic, G., Bogdan, S., 2016. Decentralized control of multi-agv systems in autonomous warehousing applications. IEEE Transactions on Automation Science and Engineering 13 (4), 1433–1447.
Ghorai, P., Majhi, S., Kasi, V. R., Pandey, S., 2018. Parameter identification of delayed under-damped systems using on-line relay autotuning. IEEE Transactions on Circuits and Systems II: Express Briefs 66 (7), 1197–1201.
Hägglund, T., J. Astr¨öm, K., 2004. Revisiting the ziegler-nichols tuning rules for pi control—part ii the frequency response method. Asian Journal of Control 6 (4), 469–482.
Hang, C., Astrom, K., Wang, Q., 2002. Relay feedback auto-tuning of process controllers—a tutorial review. Journal of process control 12 (1), 143–162.
Montonen, J.-H., Nevaranta, N., Lindh, T., Alho, J., Immonen, P., Pyrh¨onen, O., 2017. Experimental identification and parameter estimation of the mechanical driveline of a hybrid bus. IEEE Transactions on Industrial Electronics 65 (7), 5921–5930.
Nguyen, G. H., Shin, J.-H., Kim, W.-H., 2014. Autotuning controller for motion control system based on intelligent neural network and relay feedback approach. IEEE/ASME Transactions on Mechatronics 20 (3), 1138–1148.
Sánchez Moreno, J., Dormido Bencomo, S., Díaz Martínez, J. M., 2021. Fitting of generic process models by an asymmetric short relay feedback experiment—the n-shifting method. Applied Sciences 11 (4), 1651.
Skogestad, S., Grimholt, C., 2012. The simc method for smooth pid controller tuning. PID control in the third millennium: Lessons learned and new approaches, 147–175.
Soares, J. M., Navarro, I., Martinoli, A., 2016. The khepera iv mobile robot: performance evaluation, sensory data and software toolbox. In: Reis, L. P., Moreira, A. P., Lima, P. U., Montano, L., Mu˜noz-Martinez, V. (Eds.), Robot 2015: Second Iberian Robotics Conference: Advances in Robotics, Volume 1. Springer International Publishing, pp. 767–781.
Tzafestas, S. G., 2018. Mobile robot control and navigation: A global overview. Journal of Intelligent & Robotic Systems 91, 35–58.
Velázquez, R., Lay-Ekuakille, A., 2011. A review of models and structures for wheeled mobile robots: Four case studies. In: 2011 15th International Conference on Advanced Robotics (ICAR). IEEE, Tallinn, Estonia, pp. 524–529.
Yousfi Allagui, N., Salem, F. A., Aljuaid, A. M., 2021. Artificial fuzzy-pid gain scheduling algorithm design for motion control in differential drive mobile robotic platforms. Computational Intelligence and Neuroscience 2021 (1), 5542888.
Yu, C.-C., 2006. Autotuning of PID controllers: A relay feedback approach. Springer Science & Business Media.
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Copyright (c) 2025 Francisco José Mañas-Álvarez, María Guinaldo, Raquel Dormido, Sebastián Dormido
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
