Application Problems

Chapter
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

This chapter introduces the chemical reaction algorithm; it describes the main characteristics and definitions. In this work, the main objective is to introduce a novel optimization algorithm based in a paradigm inspired by nature, the chemical reactions.

Keywords

Chemical optimization Chemical reactions Function optimization 

References

  1. 1.
    Y. Kanayama, Y. Kimura, F. Miyazaki, T. Noguchi, A stable tracking control method for a non-holonomic mobile robot. in Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems.(Osaka, Japan, 1991), pp 1236–1241Google Scholar
  2. 2.
    T.-C. Lee, C.H. Lee, C.-C. Teng, Tracking control of mobile robots using the backsteping technique. in Proceedings of the 5th International Conference Control, Automation, Robotics Vision. (Singapore, Dec 1998), pp 1715–1719Google Scholar
  3. 3.
    T.-C. Lee, K. Tai, Tracking Control of Unicycle-Modeled Mobile robots Using a Saturation Feedback Controller. IEEE Trans. Control Syst. Technol. 9(2), 305–318 (2001)CrossRefGoogle Scholar
  4. 4.
    S. Bentalba, A. El Hajjaji, A. Rachid, Fuzzy control of a mobile robot: a new approach. in Proceedings of the IEEE International Conference on Control Applications, (Hartford, CT, Oct 1997), pp 69–72Google Scholar
  5. 5.
    S. Ishikawa, A method of indoor mobile robot navigation by fuzzy control. in Proceedings of the International Conference Intelligent Robotic System. (Osaka, Japan, 1991), pp. 1013–1018Google Scholar
  6. 6.
    T.H. Lee, F.H.F. Leung, P.K.S. Tam, Position control for wheeled mobile robot using a fuzzy controller. IEEE 2, 525–528 (1999)Google Scholar
  7. 7.
    S. Pawlowski, P. Dutkiewicz, K. Kozlowski, W. Wroblewski, Fuzzy logic implementation in mobile robot control. in 2nd Workshop on Robot Motion and Control, (Oct 2001), pp 65–70Google Scholar
  8. 8.
    C.-C. Tsai, H.-H. Lin, C.-C. Lin, Trajectory tracking control of a laser-guided wheeled mobile robot, in Proceedings of the IEEE International Conference on Control Applications. (Taipei, Taiwan, Sept 2004), pp 1055–1059Google Scholar
  9. 9.
    S.V. Ulyanov, S. Watanabe, V.S. Ulyanov, K. Yamafuji, L.V. Litvintseva, G.G. Rizzotto, Soft computing for the intelligent robust control of a robotic unicycle with a new physical measure for mechanical controllability, soft computing, vol. 2. (Springer, 1998), pp 73–88Google Scholar
  10. 10.
    R. Fierro, F.L. Lewis, Control of a nonholonomic mobile robot using neural networks. IEEE Trans. Neural Networks 9(4), 589–600 (1998)CrossRefGoogle Scholar
  11. 11.
    K.T. Song, L.H. Sheen, Heuristic fuzzy-neural network and its application to reactive navigation of a mobile robot. Fuzzy Sets Syst. 110(3), 331–340 (2000)CrossRefGoogle Scholar
  12. 12.
    A.M. Bloch, S. Drakunov, Tracking in nonholonomic dynamic system via sliding modes. in Proceedings IEEE Conference on Decision and Control, (Brighton, UK, 1991), pp. 1127–1132Google Scholar
  13. 13.
    D. Chwa, Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates. IEEE Trans. Control Syst. Tech. 12(4), 633–644 (2004)MathSciNetGoogle Scholar
  14. 14.
    R. Fierro, F.L. Lewis, Control of a nonholonomic mobile robot: backstepping kinematics into dynamics. in Proceedings of the 34th Conference on Decision and Control, (New Orleans, LA, 1995)Google Scholar
  15. 15.
    T. Fukao, H. Nakagawa, N. Adachi, Adaptive tracking control of a nonnholonomic mobile robot. IEEE Trans. Robot. Autom. 16(5), 609–615 (2000)CrossRefGoogle Scholar
  16. 16.
    L. Astudillo, O. Castillo, L. Aguilar, Intelligent control for a perturbed autonomous wheeled mobile robot: a type-2 fuzzy logic approach. Nonlinear Studies 14–1, 37–48 (2007)MathSciNetGoogle Scholar
  17. 17.
    R. Martinez, O. Castillo, L. Aguilar, Optimization of type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms. Inf. Sci. 179–13, 2158–2174 (2009)CrossRefGoogle Scholar
  18. 18.
    O. Castillo, R. Martinez-Marroquin, P. Melin, J. Soria, Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition, Studies in Computational Intelligence 256(2009), 247–262 (2009)Google Scholar
  19. 19.
    G. Campion, G. Bastin, B. D’Andrea-Novel, Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Trans. Robot. Autom. 12(1), 47–62 (1996)Google Scholar
  20. 20.
    W. Nelson, I. Cox, Local path control for an autonomous vehicle, in Proceedings of the IEEE Conference on Robotics and Automation, (1988), pp. 1504–1510Google Scholar

Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Leslie Astudillo
    • 1
  • Patricia Melin
    • 1
  • Oscar Castillo
    • 1
  1. 1.Division of Graduate StudiesTijuana Institute of TechnologyTijuanaMexico

Personalised recommendations