Position and Orientation Control of a Mobile Robot Using Neural Networks

  • D. Narendra Kumar
  • Halini Samalla
  • Ch. Jaganmohana Rao
  • Y. Swamy Naidu
  • K. Alfoni Jose
  • B. Manmadha Kumar
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 32)


In this paper, an adaptive neuro-control system with two levels is proposed for the motion control of a nonholonomic mobile robot. In the first level, a PD controller is designed to generate linear and angular velocities, necessary to track a reference trajectory. The proposed strategy is based on changing the robot control variables. Using this model, the nonholonomic constraints disappear and shows how the direct adaptive control theory can used to design robot controllers. In the second level, a neural network converts the desired velocities, provided by the first level, into a torque control. By introducing appropriate Lyapunov functions asymptotic stability of state variables and stability of system is guaranteed. The tracking performance of neural controller under disturbances is compared with PD controller. Sinusoidal trajectory and lemniscate trajectories are considered for this comparison.


Neural network Mobile robot 


  1. 1.
    Kolmanovsky, I., McClamroch, N.H.: Development in nonholonomic control problems. IEEE Control Syst. 15, 20–36 (1995)Google Scholar
  2. 2.
    Fukao, T., Nakagawa, H., Adachi, N.: Adaptive tracking control of a nonholonomic mobile robot. IEEE Trans. Robot. Autom. 16, 609–615 (2000)CrossRefGoogle Scholar
  3. 3.
    Fierro, R., Lewis, F.L.: Control of a nonholonomic mobile robot using neural networks. IEEE Trans. Neural Netw. 9, 589–600 (1998)CrossRefGoogle Scholar
  4. 4.
    Vieira, F.C., Medeiros, A.A.D., Alsinia, P.J., Araujo, A.P. Jr.: Position and orientation control of a two wheeled differentially driven nonholonomic mobile robotGoogle Scholar
  5. 5.
    Kar, I., Behera, L.: Direct adaptive neural control for affine nonlinear systems. Appl. Soft Comput. 9, 756–764 (2008)Google Scholar
  6. 6.
    Gholipour, A., Yazdanpanah, M.J.: Dynamic tracking control of nonholonomic mobile robot with model reference adaption for uncertain parameters. Control Intelligent Processing Center for Excellence, University of TehranGoogle Scholar
  7. 7.
    Kar, I.: Intelligent control schemes for nonlinear systems. Ph.D. thesis, Indian Institute of Technology, Kanpur, India (2008)Google Scholar
  8. 8.
    Velagic, J., Lacevic, B., Osmic, N.: Nonlinear Motion Control of Mobile Robot Dynamic Model. University of Sarajevo Bosnia and HerzegovinaGoogle Scholar
  9. 9.
    Velagic, J., Osmic, N., Lacevic, B.: Neural Network Controller for Mobile Robot Motion Control, vol. 47. World Academy of Science, Engineering and Technology (2008)Google Scholar
  10. 10.
    Zhong, X., Zhou, Y.: Establishing and maintaining wireless communication coverage among multiple mobile robots using artificial neural network. IEEE 2083–2089 (2011)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  • D. Narendra Kumar
    • 1
  • Halini Samalla
    • 1
  • Ch. Jaganmohana Rao
    • 1
  • Y. Swamy Naidu
    • 1
  • K. Alfoni Jose
    • 2
  • B. Manmadha Kumar
    • 3
  1. 1.Department of EEESri Sivani College of EngineeringSrikakulamIndia
  2. 2.Department of EEEVITS College of EngineeringSontyam, VisakhapatnamIndia
  3. 3.Department of EEEAditya Institute of Technology and ManagementTekkaliIndia

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