Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지

A Precision Control of Wheeled Mobile Robots Using Neural Network

신경회로망을 이용한 이동로봇의 정밀 제어

  • 김무진 (포항공과대학교 기계공학과) ;
  • 이영진 (부산대학교 지능기계공학과) ;
  • 박성준 (동명대학교 전기공학과) ;
  • 이만형 (부산대학교 기계공학부)
  • Published : 2000.08.01
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Abstract

In this paper we propose an eminent controller for wheeled mobile robots. This controller consists of an input-output linearization controller trying to stabilize the system and a neural network controller to compensate for uncertainties. The uncertainties are divided into two parts. First unstructured uncertainties include the elements related with system order such as friction disturbance. Second structure uncertainties are the incorrect system parameters A neural network structure of the proposed overall controller learns structural errors of the wheeled mobile robots with uncertainties and includes the neural network output. This controller learns quickly the model and has good tracking performance Simulation results show that the proposed controller is more efficient than analog controllers.

Keywords

References

  1. J. J. Hopfield, 'Neurons with graded response have collective computational abilities,' Proc. of the National Academy of Sciences, USA, vol. 79, pp. 2554-2558, 1982
  2. A. G. Barto, R. S. Sutton, and C. W. Anderson, 'Neuronlike adaptive elements that can solve difficult learning control problems,' IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-13, pp. 834-846, 1983
  3. D. E. Rumelhart, J. L. McClelland, eds., Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1, MIT Press, Cambridge, 1986
  4. D. S. Broomhead and D. Lowe, 'Multivariable functional interpolation and adaptive networks,' Complex Systems, vol. 2, pp. 321-355, 1988
  5. S. Grossberg, 'Competitive learning from interactive activation to adaptive resonance,' in Neural Networks and Natural Intelligence, S. Grossberg, (ed.), MA:MIT Press, Cambridge, 1998
  6. S. Haykin, 'Neural Networks: A Comprehensive Foundation' Prentice-Hall, New Jersey, 1999
  7. 최진영, 박현주, '신경회로망을 이용한 시스템 모델링 및 제어,' 제어.자동화.시스템공학 회지, vol. 1, no. 3, pp. 62-73, 1995
  8. F. L. Lewis, K. Liu, and A. Yesildirek, 'Neural net robot controller with guaranteed tracking performance,' IEEE Transaction on Neural Networks, vol. 6, no. 3, pp. 703-715, 1995 https://doi.org/10.1109/72.377975
  9. R. Fierro and F. L. Lewis, 'Robust practical point stabilization of a nonholonomic mobile robot using neural networks,' Journal of Intelligent and Robotic Systems, vol. 20, no. 2-4, 295-317, 1997 https://doi.org/10.1023/A:1007916529436
  10. M. Saad, P. Bigras, L. A. DEssaint, and K. Al Haddad, 'Adaptive robot control using neural networks,' IEEE Transaction on Industrial Electronics, vol. 41, no. 2, pp. 173-181, 1994 https://doi.org/10.1109/41.293877
  11. A. Ishiguro, T. Furuhashi, S. Okuma, and Y. Uchikawa, 'A neural network compensator for uncertainties of robotics manipulator,' IEEE Trans. Industrial Electronics, vol. 39, no. 6, pp. 565-570, 1992 https://doi.org/10.1109/41.170976
  12. 김성우, 이주장, '불확실성이 있는 로봇시스템의 역모델 학습에 의한 신경회로망 제어,' 제어.자동화.시스템공학 논문지, vol. 1, no. 2, pp. 88-93, 1995
  13. B. H. Nam, S. J. Lee, and S. W. Lee, 'A neural network for the trajectory control of robotic manipulators with uncertainties,' Proc. of the 1997 International Conference on Neural Networks (ICNN'97), vol. 3, pp. 1777-1780, 1997 https://doi.org/10.1109/ICNN.1997.614165
  14. Y. L. Zhang, S. A. Velinsky, and X. Feng, 'On the tracking control of differentially steered wheeled mobile robots,' Journal of Dynamic Systems, Measurement, and Control, vol. 119, 455-461, 1997
  15. N. Sarkar, X. Yun, and V. Kumar, 'Control of mechanical systems with rolling constraints: Application to dynamic control of mobile robots,' The International Journal of Robotics Research, vol. 13, no. 1, pp. 55-69, 1994 https://doi.org/10.1177/027836499401300104