Intelligent Control for an Uncertain Mobile Robot with External Disturbances Estimator

  • Yasmine KoubaaEmail author
  • Mohamed Boukattaya
  • Tarak Damak
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 270)


In this chapter, a new control approach for trajectory tracking problem of nonholonomic wheeled mobile robot (WMR) is proposed to cope with both uncertainties and external torque disturbances. The main contribution is the simultaneous exact estimation and cancelation of uncertainties and external torque disturbances without the requirement of torque measurement. First, a kinematic backstepping controller is proposed to achieve perfect velocity tracking. Then, a robust dynamic adaptive control algorithm with two update laws is developed to estimate and compensate the dynamic uncertainties and the unmeasured external torque disturbances. The design of the update laws use only position and velocity measurements and are derived from the Lyapunov stability theorem. Consequently, the proposed controllers prove that they not only can guarantee the stability and the trajectory tracking error is as small as possible but also the boundedness of all the states and signals of the closed-loop system and the convergence of the estimated disturbance to the real values. Finally, the simulation results demonstrate good tracking performance and robustness of the proposed controller.


Nonholonomic wheeled mobile robot Trajectory tracking Kinematic control Adaptive dynamic control External disturbances Uncertain parameters 



We thank the ministry of higher education and scientific research of Tunisia for funding this work.


  1. 1.
    Abadi, D.N.M., Khooban, M.H.: Design of optimal mamdani-type fuzzy controller for nonholonomic wheeled mobile robots. J. King Saud Univ-Eng. Sci. 27(1), 92–100 (2015)CrossRefGoogle Scholar
  2. 2.
    Almeida Martins, N., El’youssef, E.S., De Pieri, E.R., Lombardi, W.C., Jungers, M.: An adaptive variable structure controller for the trajectory tracking of a nonholonomic mobile robot with uncertainties and disturbances. J. Comput. Sci. Technol. 11 (2011)Google Scholar
  3. 3.
    Blaič, S.: A novel trajectory-tracking control law for wheeled mobile robots. Robot. Auton. Syst. 59(11), 1001–1007 (2011)CrossRefGoogle Scholar
  4. 4.
    Boukattaya, M., Jallouli, M., Damak, T.: On trajectory tracking control for nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances. Robot. Auton. Syst. 60(12), 1640–1647 (2012)CrossRefGoogle Scholar
  5. 5.
    Cui, M., Liu, H., Liu, W., Qin, Y.: An adaptive unscented Kalman filter-based controller for simultaneous obstacle avoidance and tracking of wheeled mobile robots with unknown slipping parameters. J. Intell. Robot. Syst. 1–16 (2017)Google Scholar
  6. 6.
    Danesh, M., Sheikholeslam, F., Keshmiri, M.: An adaptive manipulator controller based on force and parameter estimation. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 89(10), 2803–2811 (2006)CrossRefGoogle Scholar
  7. 7.
    Esmaeili, N., Alfi, A., Khosravi, H.: Balancing and trajectory tracking of two-wheeled mobile robot using backstepping sliding mode control: design and experiments. J. Intell. Robot. Syst. 87(3–4), 601–613 (2017)CrossRefGoogle Scholar
  8. 8.
    Fierro, R., Lewis, F.L.: Control of a nonholonomic mobile robot using neural networks. IEEE Trans. Neural Netw. 9(4), 589–600 (1998)CrossRefGoogle Scholar
  9. 9.
    Ghasemi, M., Nersesov, S.G., Clayton, G.: Finite-time tracking using sliding mode control. J. Frankl. Inst. 351(5), 2966–2990 (2014)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Kim, D.-H., Oh, J.-H.: Tracking control of a two-wheeled mobile robot using input-output linearization. Control Eng. Pract. 7(3), 369–373 (1999)CrossRefGoogle Scholar
  11. 11.
    Liu, Z., Chen, C., Zhang, Y., Chen, C.P.: Coordinated fuzzy control of robotic arms with actuator nonlinearities and motion constraints. Inf. Sci. 296, 1–13 (2015)CrossRefGoogle Scholar
  12. 12.
    Mohareri, O., Dhaouadi, R., Rad, A.B.: Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks. Neurocomputing 88, 54–66 (2012)CrossRefGoogle Scholar
  13. 13.
    Peng, Z., Yang, S., Wen, G., Rahmani, A., Yu, Y.: Adaptive distributed formation control for multiple nonholonomic wheeled mobile robots. Neurocomputing 173, 1485–1494 (2016)CrossRefGoogle Scholar
  14. 14.
    Pourboghrat, F., Karlsson, M.P.: Adaptive control of dynamic mobile robots with nonholonomic constraints. Comput. Electr. Eng. 28(4), 241–253 (2002)CrossRefGoogle Scholar
  15. 15.
    Rani, M., Kumar, N., Singh, H.P.: Efficient position/force control of constrained mobile manipulators. Int. J. Dyn. Control 1–10 (2018)Google Scholar
  16. 16.
    Shojaei, K., Shahri, A.M., Tarakameh, A.: Adaptive feedback linearizing control of nonholonomic wheeled mobile robots in presence of parametric and nonparametric uncertainties. Robot. Comput.-Integr. Manuf. 27(1), 194–204 (2011)CrossRefGoogle Scholar
  17. 17.
    Singh, V.K., Sharma, V., Sharma, B., Nath, R.: Synchronisation of different order chaotic systems with delay and parametric uncertainty. Int. J. Appl. Nonlinear Sci. 2(3), 184–199 (2016)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Su, K.-H.: Robust tracking control design and its application to balance a two-wheeled robot steering on a bumpy road. Proc. Inst. Mech. Eng. Part I: J. Syst. Control Eng. 226(7), 887–903 (2012)Google Scholar
  19. 19.
    Sun, T., Pei, H., Pan, Y., Zhou, H., Zhang, C.: Neural network-based sliding mode adaptive control for robot manipulators. Neurocomputing 74(14–15), 2377–2384 (2011)CrossRefGoogle Scholar
  20. 20.
    Tsai, C.-C., Cheng, M.-B., Lin, S.-C.: Robust tracking control for a wheeled mobile manipulator with dual arms using hybrid sliding-mode neural network. Asian J. Control 9(4), 377–389 (2007)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Tsai, C.-C., Li, Y.-Y., Tai, F.-C., Lu, C.-H.: Intelligent adaptive motion control using fuzzy basis function networks for electric unicycle. Asian J. Control 17(3), 977–993 (2015)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Wu, J., Xu, G., Yin, Z.: Robust adaptive control for a nonholonomic mobile robot with unknown parameters. J. Control Theory Appl. 7(2), 212–218 (2009)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Ye, J.: Tracking control for nonholonomic mobile robots: integrating the analog neural network into the backstepping technique. Neurocomputing 71(16–18), 3373–3378 (2008)CrossRefGoogle Scholar
  24. 24.
    Yue, M., Wang, S., Zhang, Y.: Adaptive fuzzy logic-based sliding mode control for a nonholonomic mobile robot in the presence of dynamic uncertainties. Proc. Inst. Mech. Eng. Part C: J. Mech. Eng. Sci. 229(11), 1979–1988 (2015)CrossRefGoogle Scholar
  25. 25.
    Yue, M., Wei, X.: Dynamic balance and motion control for wheeled inverted pendulum vehicle via hierarchical sliding mode approach. Proc. Inst. Mech. Eng. Part I: J. Syst. Control Eng. 228(6), 351–358 (2014)Google Scholar
  26. 26.
    Zhang, Y., Liu, G., Luo, B.: Finite-time cascaded tracking control approach for mobile robots. Inf. Sci. 284, 31–43 (2014). Special issue on Cloud-assisted Wireless Body Area NetworksGoogle Scholar
  27. 27.
    Zhou, B., Han, J., Dai, X.: Backstepping based global exponential stabilization of a tracked mobile robot with slipping perturbation. J. Bionic Eng. 8(1), 69–76 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Yasmine Koubaa
    • 1
    Email author
  • Mohamed Boukattaya
    • 1
  • Tarak Damak
    • 1
  1. 1.Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA)National School of Engineering of SfaxSfaxTunisia

Personalised recommendations