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Research Article

A combined backstepping and fractional-order PID controller to trajectory tracking of mobile robots

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Pages 134-141 | Received 03 Jan 2022, Accepted 23 Feb 2022, Published online: 27 Feb 2022

References

  • Gheisarnejad, M., & Khooban, M. H. (2021). An intelligent non-integer PID controller-based deep reinforcement learning: Implementation and experimental results. IEEE Transactions on Industrial Electronics, 68(4), 3609–3618. https://doi.org/10.1109/TIE.41
  • Huang, H. C., & Chiang, C. H. (2016). Backstepping holonomic tracking control of wheeled robots using an evolutionary fuzzy system with qualified ant colony optimization. International Journal of Fuzzy Systems, 18(1), 28–40. https://doi.org/10.1007/s40815-015-0106-4
  • Jiang, X., & Li, S. (2017). BAS: Beetle antennae search algorithm for optimization problems. International Journal of Robotics and Control, 1(1), 1–5. https://doi.org/10.5430/ijrc.v1n1p1
  • Khai, T., Ryoo, Y., & Gill, W. (2020). Design of kinematic controller based on parameter tuning by fuzzy inference systems for trajectory tracking of differentia-drive mobile robot. International Journal of Fuzzy Systems, 22(7), 1–7. https://doi.org/10.1007/s40815-020-00842-9
  • Li, S., Wang, Q., & Ding, L. (2020). Adaptive NN-based finite-time tracking control for wheeled mobile robots with time-varying full state constraints. Neurocomputing, 403(2), 421–430. https://doi.org/10.1016/j.neucom.2020.04.104
  • Mai, T. A., Dang, T. S., & Duong, D. T. (2021). A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(3), 1–13. https://doi.org/10.1007/s40430-020-02767-8
  • Martins, F., Sarcinelli-Filho, M., & carelli, R. (2016). A velocity-based dynamic model and its properties for differential drive mobile robots. Journal of Intelligent and Robotic Systems, 85(2), 277–292. https://doi.org/10.1007/s10846-016-0381-9
  • Saleh, A., Hussain, M., & Klim, S. (2018). Optimal trajectory tracking control for a wheeled mobile robot using fractional-order-PID-controller. Journal of University of Babylon for Engineering Sciences, 26(4), 292–306. https://doi.org/10.29196/jubes.v26i4.1087
  • Sen, P. T. H., Minh, N. Q., A, D. T. T., & Minh, P. X. (2019). A new tracking control algorithm for a wheeled mobile robot based on backstepping and herarchical sliding mode techniques. In Proceedings of First International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (pp. 25–28). IEEE.
  • Sira-Ramirez, H., Lopez-Uribe, C., & Velasco-Villa, M. (2013). Linear observer-based active disturbance rejection control of the omnidirectional mobile robot. Asian Journal of Control, 15(1), 51–63. https://doi.org/10.1002/asjc.v15.1
  • Waleed, A. O., & Hadi, A. N. (2018). Design and stability analysis of a fractional order state feedback controller for trajectory tracking of a differential drive robot. International Journal of Control, Automation and Systems, 16(6), 2790–2800. https://doi.org/10.1007/s12555-017-0234-8
  • Wang, J., Lu, Z., Chen, W., & Wu, X. (2011). An adaptive trajectory tracking control of wheeled mobile robots. In Proceedings of 6th IEEE Conference on Industrial Electronics and Applications (pp. 1156–1160). IEEE.
  • Wang, T., Yang, L., & Liu, Q. (2020). Beetle swarm optimization algorithm: Theory and application. Filomat, 34(15), 5121–5137. https://doi.org/10.2298/FIL2015121W
  • Wang, X., Zhang, G., & Neri, F. (2015). Design and implementation of membrane controllers for trajectory tracking of non-holonomic wheeled mobile robots. Integrated Computer-Aided Engineering, 23(1), 15–30. https://doi.org/10.3233/ICA-150503
  • Xu, L., Song, B., & Cao, M. (2021). An improved particle swarm optimization algorithm with adaptive weighted delay velocity. Systems Science & Control Engineering, 9(1), 188–197. https://doi.org/10.1080/21642583.2021.1891153
  • Xu, L., Song, B., Cao, M., & Xiao, Y. (2019). A new approach to optimal design of digital fractional-order PI λD μ controller. Neurocomputing, 363(6), 66–77. https://doi.org/10.1016/j.neucom.2019.06.059
  • Xue, D., Zhao, C., & Chen, Y. Q. (2006). A modified approximation method of fractional order system. In Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation (pp. 1043–1048). IEEE.
  • Yue, M., Tang, F., Liu, B., & Yao, B. (2012). Trajectory-tracking control of a nonholonomic mobile robot: Backstepping kinematics into dynamics with uncertain disturbances. Applied Artificial Intelligence, 26(10), 952–966. https://doi.org/10.1080/08839514.2012.731347
  • Zhang, L., Liu, L., & Zhang, S. (2020). Design, implementation, and validation of robust fractional-order PD controller for wheeled mobile robot trajectory tracking. Complexity, 2020(4), 1–12. https://doi.org/10.1155/2020/9523549
  • Zhao, H., Song, B., Zhang, J., & Xu, L. (2017). Fractional order PID controller design based on PSO algorithm. Journal of Shandong University of Science and Technology (Natural Science), 36(4), 60–65.
  • Zou, L., Wang, Z., Hu, J., & Zhou, D. H. (2020). Moving horizon estimation with unknown inputs under dynamic quantization effects. IEEE Transactions on Automatic Control, 65(12), 5368–5375. https://doi.org/10.1109/TAC.9
  • Zou, L., Wang, Z., & Zhou, D. H. (2020). Moving horizon estimation with non-uniform sampling under component-based dynamic event-triggered transmission. Automatica, 120(3), Article number 109154. https://doi.org/10.1016/j.automatica.2020.109154