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Dynamic Tracking Control of Mobile Robots Using an Improved Radial Basis Function Neural Network

  • Shirong Liu
  • Qijiang Yu
  • Jinshou Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

A novel dynamic control scheme for nonholonomic mobile robots is developed in this paper. The dynamics of mobile robot based on improved radial basis function neural network (IRBFNN) is modeled online by the improved algorithm of resource allocating network (IRAN). The control scheme of mobile robot integrates a velocity controller based on backstepping technology and a torque controller based on the IRBFNN and robust compen-sator. The simulations have shown that the control system is competent for the robust tracking control of mobile robot.

Keywords

Mobile Robot Tracking Control Radial Basis Function Neural Network Radial Basis Function Network Hide Unit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Kanayama, Y., Kimura, Y., Miyazaki, F., Noguchi, T.: A Stable Tracking Control Method for an Autonomous Mobile Robot. In: Proc. IEEE Conf. Robotics and Automa., pp. 384–389 (1990)Google Scholar
  2. 2.
    Fierro, R., Lewis, F.L.: Control of Nonholonomic Mobile Robot Using Neural Networks. IEEE Transactions on Neural Networks 9, 589–600 (1998)CrossRefGoogle Scholar
  3. 3.
    Saha, A., Keeler, J.D.: Algorithms for Better Representation and Faster Learning in Radial Basis Function Network. In: Touretzky, D.S. (ed.) Advances in Neural Information Processing Systems, vol. 2, pp. 482–489. Morgan Kaufmann, San Mateo (1990)Google Scholar
  4. 4.
    Kubat, M.: A Hyperrectangle-Based Method that Creates RBF Networks. In: Howlett, R., Jain, L. (eds.) Radial Basis Function Networks, vol. 1, pp. 32–50. Physica, Heidelberg (2001)Google Scholar
  5. 5.
    Platt, C.J.: A Resource Allocating Network for Function Interpolation. Neural Computation 4, 473–493 (1991)Google Scholar
  6. 6.
    Slotine, J.J.E., Li, W.: Adaptive Nonlinear Control. Prentice-Hall, NJ (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shirong Liu
    • 1
  • Qijiang Yu
    • 1
    • 2
  • Jinshou Yu
    • 2
  1. 1.College of AutomationHangzhou Dianzi UniversityHangzhouChina
  2. 2.Research Institute of AutomationEast China University of Science and TechnologyShanghaiChina

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