Adaptive Backsteeping SMC with Cuckoo Search Algorithm for Two Wheeled Self Balancing Robot

  • Authors

    • Asst. Pro.Dr.Ekhlas H.Karam
    • Noor. M.Mjeed
    2018-07-27
    https://doi.org/10.14419/ijet.v7i3.13.16318
  • BS, BS-SMC, CS, RBFNN, Two wheeled self balancing robot.

  • Abstract

    In this paper, a robust Radial Basis Function (RBF) Backstepping Sliding Mode controller (BS-SMC) is successfully developed for the attitude stabilization and tracking the trajectory of two wheeled self-balancing mobile robot under the external disturbance and uncertainty. The design of BS control is derived based on Lyapunov function to ensure the stability of the robot system and the SMC is designed with a switching function in order to attenuate the effects of the disturbances,   the auto-adjustable RBF inference system is suggested to estimate the equivalent component of the BS-SMC to treat the model dependency problem and robustness improvement. Also a cuckoo search (CS) optimization algorithm is used to determine the optimal values of the backsteeping sliding mode controller. Numerical simulations show the efficiency of the suggested controller in handling the balance and tracking problems of the two wheeled self-balancing mobile robot

     

     

  • References

    1. [1] Liu, K., Bai, M., & Ni, Y., (2011), Two-wheel self-balanced car based on Kalman filtering and PID algorithm, IEEE 18th International Conference on Industrial Engineering and Engineering Management, Changchun, pp. 281-285.

      [2] Sun, L. & GAN J. (2010), Researching of Two-Wheeled Self-Balancing Robot Base on LQR Combined with PID,pp. 1-5.

      [3] Memarbashi, Hamid R, & Jen-YuanChang (2011), Design and Parametric Control of Co-axes Driven Two-Wheeled Balancing Robot. New Zealand, the Massey University,MSc Thesis June 01.

      [4] Kachroo, P., & Tomizuka, M.. (1996), Chattering Reduction and Error Convergence in the Sliding-Mode Control of a Class of Nonlinear Systems. IEEE TRANSACTIONS ON AUTOMATIC CONTROL AC,41 (7): 1063-1067.

      [5] Fuquan, D., Fangxing, L., Yang, B., Wenzeng, G., Chengguo, Z., Xueshan, G.,(2012), Development of a Coaxial Self-Balancing Robot Based on Sliding Mode Control. IEEE International Conference on Mechatronics and Automation (ICMA),1241-1246.

      [6] Song, Y., Guo, L., Xing, B., (2016), Cascade sliding mode and RBF network self-adaption controller design for a two-wheeled robot. 1659-1663.

      [7] Nguyen Gia Minh Thao; Duong Hoai Nghia, Nguyen Huu Phuc (2010), A PID Backstepping Controller for Two-Wheeled Self-Balancing Robot.78-81.

      [8] Son, N. N., & Anh, H. P. H. (2014), Adaptive Backstepping Self-balancing Control of a Two-wheel Electric Scooter. International Journal of Advanced Robotic Systems,11(10):1-11.

      [9] Anh, H. P. H., & Son, N. N., (2015), Hybrid PD and adaptive backstepping control for self-balancing two-wheel electric scooter. Journal of Computer Science and Cybernetics, 30(4): 347–360.

      [10] Tsai, C.-C., Shang-Yu, J., & Shih-Min, H., (2010), Trajectory tracking of a self-balancing two-wheeled robot using backstepping sliding-mode control and fuzzy basis function networks. IEEE/RSJ International Conference on Intelligent Robots and Systems ,3943-3948.

      [11] Esmaeili, N., Alfi, A., & Khosravi, H.(2017), Balancing and Trajectory Tracking of Two-Wheeled Mobile Robot Using Backstepping Sliding Mode Control: Design and Experiments. journal of Intelligent and Robotic Systems: Theory and Applications, 87(3): 601-613.

      [12] Qin, Y., Liu, Y., Zang, X., & Liu, J., (2011),Balance control of two-wheeled self-balancing mobile robot based on TS fuzzy model. International Forum on Strategic Technology (IFOST), 406-409.

      [13] Prakash, K., &Thomas, K., (2016), Study of Controllers for A Two wheeled Self-Balancing Robot. International Conference on Next Generation Intelligent Systems (ICNGIS),1-7.

      [14] Jamil, O., Jamil, M., Ayaz, Y., Ahmad, K., (2014), Modeling, Control of a Two-Wheeled Self- Balancing Robot. International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE), 191-199.

      [15] Qu, C., & He, W., (2015), A double Mutation Cuckoo Search Algorithm for Solving Systems of Nonlinear Equations. International Journal of Hybrid Information Technology,8(12): 433-448.

      [16] Yang, Xin-She, & Deb, Suash.,(2009), Cuckoo search via Lévy Flights. IEEE Publications, 210-214.

      [17] Wang, R., Zhao, Y.,& Sun, J.(2016), Application of optimized RBF neural network in ship's autopilot design. IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC),1642-1646.

      [18] Yong Tao, Jiaqi Zheng, &Yuanchang Lin (2016), A Sliding Mode Control-based on a RBF Neural Network for Deburring Industry Robotic Systems. International Journal of Advanced Robotic Systems, 13(1): 1-10.

      [19] Hung-Ching, L., Cheng-Hung, T.,& Ming-Hung, C., (2010), Radial Basis Function Neural Network with Sliding Mode Control for Robotic Manipulators. IEEE International Conference on Systems, Man and Cybernetics-SMC, 1209-1215.

  • Downloads

  • How to Cite

    Pro.Dr.Ekhlas H.Karam, A., & M.Mjeed, N. (2018). Adaptive Backsteeping SMC with Cuckoo Search Algorithm for Two Wheeled Self Balancing Robot. International Journal of Engineering & Technology, 7(3.13), 27-32. https://doi.org/10.14419/ijet.v7i3.13.16318

    Received date: 2018-07-26

    Accepted date: 2018-07-26

    Published date: 2018-07-27