NEURO-ADAPTIVE DYNAMIC CONTROL FOR TRAJECTORY TRACKING OF MOBILE ROBOTS

Marvin K. Bugeja, Simon G. Fabri

Abstract

This paper presents a novel functional-adaptive dynamic controller for trajectory tracking of nonholonomic wheeled mobile robots. The controller is developed in discrete-time and employs a Gaussian radial basis function neural network for the estimation of the robot’s nonlinear dynamic functions, which are assumed to be completely unknown. Optimal on-line weight tuning is achieved by employing the Kalman filter algorithm, based on a specifically formulated stochastic inverse dynamic identification model of the mobile base. A discrete-time dynamic control law employing the estimated functions is proposed and cascaded with a trajectory tracking kinematic controller. The performance of the complete system is analysed and compared by realistic simulations.

References

  1. Brockett, R. W. (1983). Asymptotic Stability and Feedback Stabilisation. Differential Geometric Control Theory. Birkhauser, Boston, MA.
  2. Bugeja, M. K. and Fabri, S. G. (2005). Multilayer perceptron functional adaptive control for trajectory tracking of wheeled mobile robots. In Proc. 2nd International Conference on Informatics in Control, Automation and Robotics (ICINCO2005), volume 3, pages 66-72, Barcelona, Spain.
  3. Canudas de Wit, C., Khennoul, H., Samson, C., and Sordalen, O. J. (1993). Nonlinear control design for mobile robots. In Zheng, Y. F., editor, Recent Trends in Mobile Robots, Robotics and Automated Systems, chapter 5, pages 121-156. World Scientific.
  4. Corradini, M. L., Ippoliti, G., and Longhi, S. (2003). Neural networks based control of mobile robots: Development and experimental validation. Journal of Robotic Systems, 20(10):587-600.
  5. Corradini, M. L. and Orlando, G. (2001). Robust tracking control of mobile robots in the presence of uncertainties in the dynamic model. Journal of Robotic Systems, 18(6):317-323.
  6. Crowley, J. L. (1989). Asynchronous control of orientation and displacement in a robot vehicle. In Proc. of the 1989 IEEE International Conference on Robotics and Automation (Vol. 3), pages 1277-1282, Scottsdale, AZ.
  7. de Sousa, C., Hemerly, E. M., and Galvao, R. K. H. (2002). Adaptive control for mobile robot using wavelet networks. IEEE Transactions on Systems, Man and Cybernetics, 32(4):493-504.
  8. Ding, D. and Cooper, R. A. (2005). Electric-powered wheelchairs. IEEE Control Systems Magazine, 25(2):22-34.
  9. Fabri, S. G. and Kadirkamanathan, V. (1998). Dual adaptive control of nonlinear stochastic systems using neural networks. Automatica, 34(2):245-253.
  10. Fabri, S. G. and Kadirkamanathan, V. (2001). Functional Adaptive Control: An Intelligent Systems Approach. Springer-Verlag, London, UK.
  11. Fierro, R. and Lewis, F. L. (1995). Control of a nonholonomic mobile robot: Backstepping kinematics into dynamics. In Proc. IEEE 34th Conference on Decision and Control (CDC'95), pages 3805-3810, New Orleans, LA.
  12. Fierro, R. and Lewis, F. L. (1998). Control of a nonholonomic mobile robot using neural networks. IEEE Trans. Neural Networks, 9(4):589-600.
  13. Fukao, T., Nakagawa, H., and Adachi, N. (2000). Adaptive tracking control of a nonholonomic mobile robot. IEEE Transactions on Robotics and Automation, 16(5):609-615.
  14. Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Trans. ASME J. Basic Eng., 82:34-45.
  15. Kanayama, Y., Kimura, Y., Miyazaki, F., and Noguchi, T. (1990). A stable tracking control method for an autonomous mobile robot. In Proc. IEEE International Conference of Robotics and Automation, pages 384- 389, Cincinnati, OH.
  16. Kolmanovsky, I. and McClamroch, N. H. (1995). Developments in nonholonomic control problems. IEEE Control Systems Magazine, 15(6):20-36.
  17. Lamiraux, F., Laumond, J. P., VanGeem, C., Boutonnet, D., and Raust, G. (2005). Trailer truck trajectory optimization: the transportation of components for the Airbus A380. IEEE Robotics and Automation Magazine, 12(1):14-21.
  18. Maybeck, P. S. (1979). Stochastic Models, Estimation and Control, volume 141-1 of Mathematics in Science and Engineering. Academic Press Inc., London, UK.
  19. Oubbati, M., Schanz, M., and Levi, P. (2005). Kinematic and dynamic adaptive control of a nonholonomic mobile robot using RNN. In Proc. IEEE Symposium on Computational Intelligence in Robotics and Automation (CIRA'05), Helsinki, Finland.
  20. Poggio, T. and Girosi, F. (1990). Networks for approximation and learning. Proc. IEEE, 78(9):1481-1497.
  21. Sarkar, N., Yun, X., and Kumar, V. (1994). Control of mechanical systems with rolling constraints: Applications to dynamic control of mobile robots. International Journal of Robotics Research, 13(1):55-69.
  22. van de Water, H. and Willems, J. C. (1981). The certainty equivalence property in stochastic control theory. IEEE Transactions on Automatic Control, AC26(5):1080-1087.
Download


Paper Citation


in Harvard Style

Bugeja M. and Fabri S. (2006). NEURO-ADAPTIVE DYNAMIC CONTROL FOR TRAJECTORY TRACKING OF MOBILE ROBOTS . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 404-411. DOI: 10.5220/0001218904040411


in Bibtex Style

@conference{icinco06,
author={Marvin K. Bugeja and Simon G. Fabri},
title={NEURO-ADAPTIVE DYNAMIC CONTROL FOR TRAJECTORY TRACKING OF MOBILE ROBOTS},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={404-411},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001218904040411},
isbn={978-972-8865-60-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - NEURO-ADAPTIVE DYNAMIC CONTROL FOR TRAJECTORY TRACKING OF MOBILE ROBOTS
SN - 978-972-8865-60-3
AU - Bugeja M.
AU - Fabri S.
PY - 2006
SP - 404
EP - 411
DO - 10.5220/0001218904040411