Have a personal or library account? Click to login
Research on A Robust Adaptive Controller with Disturbance Observer For Wheeled Mobile Robot Cover

Research on A Robust Adaptive Controller with Disturbance Observer For Wheeled Mobile Robot

Open Access
|Mar 2026

References

  1. R. Raj and A. Kos, ”A Comprehensive Study of Mobile Robot: History, Developments, Applications, and Future Research Perspectives”, Applied Sciences., vol. 12, no. 14, 2022. DOI: 10.3390/app12146951
  2. I. Doroftei and F. Adăscăliţei, ”PRACTICAL APPLICATIONS FOR MOBILE ROBOTS BASED ON MECANUM WHEELS - A SYSTEMATIC SURVEY”, The Romanian Review of Precision Mechanics, Optics and Mechatronics., no. 40, 2011, 21–29.
  3. C. Mireles, M. Sanchez, D. Cruz-Ortiz, I. Salgado, and I. Chairez, ”Home-care nursing controlled mobile robot with vital signal monitoring”, Medical & Biological Engineering & Computing., vol. 61, no. 2, 2023, 399–420. DOI: 10.1007/s11517-022-02712-y
  4. O. Buckmann, M. Krömker, and U. Berger, ”An Application Platform for the Development and Experimental Validation of Mobile Robots for Health Care Purposes”, Journal of Intelligent and Robotic Systems., vol. 22, no. 3, 1998, 331–350. DOI: https://doi.org/10.1023/A:1007945702881
  5. R. Galati, G. Mantriota, and G. Reina, ”Adaptive heading correction for an industrial heavy-duty omnidirectional robot”, (in eng), Sci Rep., vol. 12, no. 1, 2022, 19608. DOI: 10.1038/s41598-022-24270-x
  6. C. Patruno, V. Renò, M. Nitti, N. Mosca, M. di Summa, and E. Stella, ”Vision-based omnidirectional indoor robots for autonomous navigation and localization in manufacturing industry”, Heliyon., vol. 10, no. 4, p. e26042, 2024. DOI: 10.1117/12.2595511
  7. J. P. Trevelyan, S.-C. Kang, and W. R. Hamel, ”Robotics in Hazardous Applications”, in Springer Handbook of Robotics., B. Siciliano and O. Khatib, Heidelberg: Springer Berlin Heidelberg, 2008, 1101–1126. DOI: 10.1007/978-3-319-32552-1_58
  8. H. Taheri and C. X. Zhao, ”Omnidirectional mobile robots, mechanisms and navigation approaches,” Mechanism and Machine Theory., vol. 153, 2020, 103958. DOI: 10.1016/j.mechmachtheory.2020.103958
  9. L. Wijayathunga, A. Rassau, and D. Chai, ”Challenges and Solutions for Autonomous Ground Robot Scene Understanding and Navigation in Unstructured Outdoor Environments: A Review”, Applied Sciences., vol. 13, no. 17. DOI:10.3390/app13179877
  10. S. A. Ahmed and M. G. Petrov, ”Trajectory Control of Mobile Robots using Type-2 Fuzzy-Neural PID Controller”, IFAC-PapersOnLine., vol. 48, no. 24, 2015. DOI: https://doi.org/10.1177/09596518251322228
  11. K. Al-Mutib and F. Abdessemed, ”Indoor mobile robot navigation in unknown environment using fuzzy logic based behaviors”, Adv. Sci. Technol. Eng. Syst. J., vol. 2, no. 3, 327–337, 2017. DOI: https://dx.doi.org/10.25046/aj020342
  12. Y.-H. Chen and Y.-Y. Chen, ”Nonlinear Adaptive Fuzzy Control Design for Wheeled Mobile Robots with Using the Skew Symmetrical Property”, Symmetry., vol. 15, no. 1. DOI: 10.3390/sym15010221
  13. G. Zidani, S. Drid, L. Chrifi-Alaoui, A. Benmakhlouf, and S. Chaouch, ”Backstepping controller for a wheeled mobile robot”, in 2015 4th International Conference on Systems and Control (ICSC), 2015, 443–448. DOI: 10.1109/ICoSC.2015.7153286
  14. G. Yanfeng, Z. Hua, and Y. Yanhui, ”Back-Stepping and Neural Network Control of a Mobile Robot for Curved Weld Seam Tracking”, Procedia Engineering., vol. 15, 2011, 38–44. DOI: https://doi.org/10.1016/j.proeng.2011.08.009
  15. M. A. Moqbel Obaid, A. R. Husain, and A. A. Mohammed Al-kubati, ”Robust Backstepping Tracking Control of Mobile Robot Based on Nonlinear Disturbance Observer”, International Journal of Electrical and Computer Engineering (IJECE)., vol. 6, no. 2, 2016. DOI: 10.11591/ijece.v6i2. pp. 901–908
  16. S. A. Tchenderli-Baham, F. Hamerlain, and N. Saadia, ”Adaptive sliding mode for the control of a wheeled mobile robot”, in 2015 15th International Conference on Control, Automation and Systems (ICCAS), 2015, 699–703. DOI: https://doi.org/10.1109/ICCAS.2015.73650
  17. Y. Jinhua, Y. Suzhen, and J. Xiao, ”Trajectory Tracking Control of WMR Based on Sliding Mode Disturbance Observer with Unknown Skidding and Slipping”, in 2017 2nd International Conference on Cybernetics, Robotics and Control (CRC), 2017, 18–22. DOI: 10.1109/CRC.2017.40
  18. A. Filipescu, V. Minzu, B. Dumitrascu, and E. Minca, ”Trajectory-tracking and discrete-time sliding-mode control of wheeled mobile robots”, in 2011 IEEE International Conference on Information and Automation, 2011, 27–32. DOI: 10.1109/ICINFA.2011.5948958
  19. J. Meng, H. Xiao, L. Jiang, Z. Hu, L. Jiang, and N. Jiang, ”Adaptive Model Predictive Control for Mobile Robots with Localization Fluctuation Estimation”, (in eng), Sensors (Basel)., vol. 23, no. 5, 2023. DOI: https://doi.org/10.3390/s23052501
  20. L. Jiang, S. Wang, Y. Xie, S. Q. Xie, S. Zheng, and J. Meng, ”Fractional robust finite time control of four-wheel-steering mobile robots subject to serious time-varying perturbations”, Mechanism and Machine Theory., vol. 169, 2022,104634. DOI: 10.1016/j.mechmachtheory.2021.104634
  21. İ. Ünal, Ö. Kabaş, O. Eceoğlu, and G. Moiceanu, ”Adaptive Multi-Robot Communication System and Collision Avoidance Algorithm for Precision Agriculture”, Applied Sciences., vol. 13, no. 15, 2023, 8602. DOI: https://doi.org/10.3390/app13158602
  22. Z. Cao, J. Song and Y. Niu, ”Finite-time sliding mode control of Markovian jump systems subject to actuator nonlinearities and its application to wheeled mobile manipulator”, Journal of the Franklin Institute., vol. 355, no. 16, 2018, 7865-7894. DOI: 10.1109/TAC.2019.2926156
  23. L. Ding, S. Li, Y. J. Liu, H. Gao, C. Chen, and Z. Deng, ”Adaptive Neural Network-Based Tracking Control for Full-State Constrained Wheeled Mobile Robotic System”, IEEE Transactions on Systems, Man, and Cybernetics: Systems., vol. 47, no. 8, 2017, 2410–2419. DOI: 10.1109/TSMC.2017.2677472
  24. K. Shojaei, ”Neural adaptive output feedback formation control of type (m, s) wheeled mobile robots,” IET Control Theory & Applications., vol. 11, no. 4, 2017, 504–515. DOI: https://doi.org/10.1049/iet-cta.2016.0952
  25. Z. Peng, S. Yang, G. Wen, A. Rahmani, and Y. Yu, ”Adaptive distributed formation control for multiple nonholonomic wheeled mobile robots”, Neurocomputing., vol. 173, 2016, 1485–1494. DOI: https://doi.org/10.1016/j.neucom.2015.09.022
  26. M. Begnini, D. W. Bertol, and N. A. Martins, ”A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results”, Control Engineering Practice, vol. 64, 2017, 27–43. DOI: https://doi.org/10.1016/j.conengprac.2017.04.006
  27. L. Xin, Q. Wang, J. She, and Y. Li, ”Robust adaptive tracking control of wheeled mobile robot”, Robotics and Autonomous Systems., vol. 78, 2016, 36–48. DOI: https://doi.org/10.1016/j.robot.2016.01.002
  28. H. Fang, Y. Zhu, S. Dian, G. Xiang, R. Guo, and S. Li, ”Robust tracking control for magnetic wheeled mobile robots using adaptive dynamic programming”, ISA Transactions., vol. 128, 2022, 123–132. DOI: 10.1016/j.isatra.2021.10.017
  29. S. Peng and W. Shi, ”Adaptive Fuzzy Output Feedback Control of a Nonholonomic Wheeled Mobile Robot”, IEEE Access., vol. 6, 2018,. DOI:10.1109/ACCESS.2018.2862163
  30. J. T. Huang and Y. L. Sung, ”Adaptive beck-stepping dynamic surface tracking control of nonholonomic mobile robots”, in 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), 2016, 1026–1031. DOI: 10.1109/ICIEA.2016.7603733
  31. D. E. Kim, H. N. Yoon, K. S. Kim, M. S. Sreejith, and J. M. Lee, ”Using current sensing method and fuzzy PID controller for slip phenomena estimation and compensation of mobile robot,” in 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2017, 397–401. DOI: 10.5772/intechopen.110497
  32. M. Chen, ”Disturbance Attenuation Tracking Control for Wheeled Mobile Robots With Skidding and Slipping”, IEEE Transactions on Industrial Electronics., vol. 64, no. 4, 2017, pp. 3359–3368. DOI: 10.1109/TIE.2016.2613839
  33. N. T.-T. Vu, L. X. Ong, N. H. Trinh, and S. T. Huong Pham, ”Robust adaptive controller for wheel mobile robot with disturbances and wheel slips”, International Journal of Electrical and Computer Engineering (IJECE)., vol. 11, no. 1, 2021, 11. DOI: 10.11591/ijece.v11i1.pp336-346
  34. W. H. Chen, J. Yang, L. Guo, and S. Li, ”Disturbance-Observer-Based Control and Related Methods–An Overview”, IEEE Transactions on Industrial Electronics., vol. 63, no. 2, 2016, 1083–1095. DOI: 10.1109/TIE.2015.2478397
DOI: https://doi.org/10.14313/jamris-2026-001 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
Language: English
Page range: 1 - 13
Submitted on: Sep 16, 2024
|
Accepted on: Nov 4, 2025
|
Published on: Mar 31, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Trong Tai Nguyen, Doan Phuc An Nguyen, Dai Nghia Tran, Phuc Bao Nguyen Nguyen, Thanh Dat Mai, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.