ENHANCED EXTENDED STATE OBSERVER BASED OUTPUT-FEEDBACK TRACKING CONTROL OF WHEELED MOBILE ROBOT WITH DISTURBANCE

Bo Qin, Huaicheng Yan, Lu Zeng, Simon X. Yang, and Meng Wang

References

  1. [1] L. Ssebazza and Y.-J. Pan, DGPS-based localization andpath following approach for outdoor wheeled mobile robots,International Journal of Robotics and Automation, 30(6), 2015,13–25.
  2. [2] P. Li, H. Yang, and S. Wang, Model predictive tracking controlwith disturbance compensation for wheeled mobile robots in anenvironment with obstacles, Journal of the Franklin Institute,360(10),2023,6669–6692.
  3. [3] S. Chang, Y. Wang, Z. Zuo, and X. Luo, Prescribed-timeformation control for wheeled mobile robots with time-varyingsuper-twisting extended state observer, Applied Mathematicsand Computation, 457, 2023, 128189.
  4. [4] W. Abbasi, F. ur Rehman, I. Shah, and A. Rauf, Stabilizingcontrol algorithm for nonholonomic wheeled mobile robotsusing adaptive integral sliding mode, International Journal ofRobotics and Automation,34(2), 2019, 1–8.
  5. [5] S. Gao, D. Zhao, X. Yan, and S.K. Spurgeon, Model-free adap-tive state feedback control for a class of nonlinear systems, IEEETransactions on Automation Science and Engineering,2023,1–13,DOI: https://doi.org/10.1109/TASE.2023.3237811.
  6. [6] B. Guo, S. Dian, T. Zhao, and X. Wang, Dynamic event-drivenneural network-based adaptive fault-attack-tolerant control forwheeled mobile robot system, ISA Transactions,140, 2023,71–83.
  7. [7] L.-H. Ying and J.-W. Zhu, Fault-tolerant tracking control formobile robotsbased on the framework of intermediate estimatorand MPC, IEEE 12th Data Driven Control and LearningSystems Conference (DDCLS),Xiangtan, China, 2023, 324–329.
  8. [8] S. Li, Q. Wang, L. Ding, X. An, H. Gao, Y. Hou, andZ. Deng, Adaptive NN-based finite-time tracking control forwheeled mobile robots with time-varying full state constraints,Neurocomputing,403,2020, 421–430.
  9. [9] M. Homayounzade and M. Alipour, Output feedback adaptivecontrol of dynamically positioned surface vessels: a disturbanceobserver-based control approach, International Journal ofRobotics and Automation, 34(4), 2019.
  10. [10] B. Moudoud, H. Aissaoui, and M. Diany, Fixed-Time non-singular fast TSM control for WMR with disturbance observer,IFAC-PapersOnLine, 55(12), 2022, 647–652.
  11. [11] L. Zhao, J. Li, H. Li, and B. Liu, Double-loop tracking controlfor a wheeled mobile robot with unmodeled dynamics alongright angle roads, ISA Transactions, 136, 2023, 525–534.
  12. [12] C. Huang, C. Luo, Y. Li, and T. Zhang, Differential flatnessactive disturbance rejection control approach for a class ofnonlinear uncertain systems, International Journal of Roboticsand Automation, 34(2), 2019.
  13. [13] J. Yang, Y. Zeng, and Y. Yin, Adaptive robust controlwith extended state observer for human–robot impedance,International Journal of Robotics and Automation, 35(1), 2020.
  14. [14] B. Moudoud, H. Aissaoui, and M. Diany, Extended stateobserver-based finite-time adaptive sliding mode control forwheeled mobile robot, Journal of Control and Decision,9(4),2022,465–476..7
  15. [15] M. Fu, L. Yu, and Y. Tuo, Extended state observer-baseddistributed formation control for autonomous surface vesselswith uncertain disturbances, International Journal of Roboticsand Automation, 33(1), 2018.
  16. [16] B. Qin, H. Yan, H. Zhang, Y. Wang, and S.X. Yang, Enhancedreduced-order extended state observer for motion controlof differential driven mobile robot, IEEE Transactions onCybernetics, 53(2), 2023, 1299–1310
  17. [17] K. Wang, Y. Liu, C. Huang, and P. Cheng, Adaptivebackstepping control with extended state observer forwheeled mobile robot, Proc.39th Chinese Control Conference(CCC),Shenyang, China, 2020, 1981–1986.
  18. [18] C. Cheng, L. Li, Q. Han, H. Ma, C. Wang, and S. Bi,Adaptive sliding mode ADRC for attitude tracking withactuator saturation and uncertainties, International Journalof Robotics and Automation, 36(5),2021,337–344.
  19. [19] S. Chang, Y. Wang, Z. Zuo, and H. Yang, Fixed-time formationcontrol for wheeled mobile robots with prescribed performance,IEEE Transactions on Control Systems Technology, 30(2),2022, 844–851.
  20. [20] S. Chang, Y. Wang, and Z. Zuo, Formation control forwheeled mobile robots with finite-time active disturbancerejection control, Proc.IEEE International Conference on Real-time Computing and Robotics (RCAR),Irkutsk, Russia, 2019,818–822.
  21. [21] J. Wang, C. Yang, J. Xia, Z.-G. Wu, and H. Shen, Observer-based sliding mode control for networked fuzzy singularlyperturbed systems under weighted try-once-discard protocol,IEEE Transactions on Fuzzy Systems, 30(6),2022,1889–1899.
  22. [22] Z. Gao, On the centrality of disturbance rejection in automaticcontrol, ISA Transactions, 53(4),2014,850–857.
  23. [23] J. Han, From PID to active disturbance rejection control, IEEETransactions on Industrial Electronics, 56(3), 2009, 900–906.
  24. [24] E. D. Sontag and Y. Wang, On characterizations of theinput-to-state stability property, Systems & Control Letters,24(5),1995,351–359.
  25. [25] J. Sun, J. Yang, S. Li, and W. X. Zheng, Output-baseddynamic event-triggered mechanisms for disturbance rejectioncontrol of networked nonlinear systems, IEEE Transactions onCybernetics, 50(5),2020,1978–1988.
  26. [26] J. Cheng, L. Xie, D. Zhang, and H. Yan, Novel event-triggeredprotocol to sliding mode control for singular semi-Markov jumpsystems, Automatica, 151,2023,110906.
  27. [27] Z. Ye, D. Zhang, C. Deng, H. Yan, and G. Feng, Finite-timeresilient sliding mode control of nonlinear UMV systems subjectto DoS attacks, Automatica, 156,2023,111170.

Important Links:

Go Back