Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2006.12.11.1081

Hybrid Sliding Mode Control of 5-link Biped Robot in Single Support Phase Using a Wavelet Neural Network  

Kim, Chul-Ha (연세대학교 전기전자공학과)
Yoo, Sung-Jin (연세대학교 전기전자공학과)
Choi, Yoon-Ho (경기대학교 전자공학부)
Park, Jin-Bae (연세대학교 전기전자공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.12, no.11, 2006 , pp. 1081-1087 More about this Journal
Abstract
Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.
Keywords
hybrid adaptive control; wavelet neural network; biped robot; sliding mode control;
Citations & Related Records
연도 인용수 순위
  • Reference
1 E. Kim, 'Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic,' IEEE Trans. Fuzzy Systems, vol. 12, no. 3, pp. 368-378, 2004   DOI   ScienceOn
2 J. Zhang, G. G. Walter, Y. Miao, and W. N. W. Lee, 'Wavelet neural networks for function learning,' IEEE Trans. Signal Processing, vol. 43, no. 6, pp. 1485-1497, 1995   DOI   ScienceOn
3 Q. Zhang and A. Benveniste, 'Wavelet networks,' IEEE Trans. Neural Network, vol. 3, no. 6, pp. 990-898, 1992   DOI   ScienceOn
4 S. S. Ge, C. C. Hang, and T. Zhang, 'Adaptive neural network control by state and output feedback,' IEEE Trans. Syst., Man, Cybern., vol. 29, no. 12, pp. 818-828, 1999   DOI   ScienceOn
5 C.M Lin and C.F Hsu, 'Neural network hybrid control for antilock braking systems,' IEEE Trans. Neural Networks, vol. 14, no. 2, pp. 351-359, 2003   DOI   ScienceOn
6 K. J. Astrom and B. Wittenmark, Adaptive Control, Addison-Wesley, 1995
7 S. Tzafestas, M. Raibert, and C. Tzafestas, 'Robust sliding-mode control applied to a 5-link biped robot,' Jour. of Intelligent and Robotic Systems, vol. 15,pp.67-133, 1996   DOI
8 O. Omidvar and D. L. Elliott, Neural Systems for Control, Academic, 1997
9 B. Delyon, A. Juditsky and A. Benveniste, 'Accuracy analysis for wavelet approximations,' IEEE Trans. Neural Networks, vol. 6, no. 3, pp. 332-348, 1995   DOI   ScienceOn
10 J. R. Noriega and H. Wang, 'A direct adaptive neural-network control for nonlinear systems and its application,' IEEE Trans. Neural Networks, vol. 9, no. 9, pp. 27-34, 1998   DOI   ScienceOn
11 H. Miura and M. Masubuchi, 'A theoretically motivated reduced-order model for the control of dynamic biped locomotion,' ASME J. Dyn. Syst. Meas. Contr., vol. 109, pp. 155-163, 1987   DOI
12 X. Mu, and Q. Wu, 'Development of a complete dynamic model of a planar five-link biped and sliding mode control of its locomotion during the double support phase,' Int. Jour. of Control, vol. 77, no. 8, pp. 789-799, 2004   DOI   ScienceOn
13 J. J. Slotine and W. Li, Applied Nonlinear Control, Prentice Hall, 1991
14 H. Miura and M. Masubuchi, 'Control of a dynamic biped locomotion system for steady walking,' ASME J. Dyn. Syst. Meas. Contr., vol. 108, pp. 111-118, 1986   DOI
15 J. Furusho and I. Shinoyama, 'Dynamic walk of a biped,' Int'l. Jour. Robotics Res., vol. 3, no. 2, pp. 60-74 1984   DOI   ScienceOn
16 H. Hemami, C. Wil, and G. L. Goliday 'The inverted pendulum and biped stability,' Math. Biosci. vol. 34 pp. 93-108, 1977   DOI   ScienceOn
17 S. Mochon, 'A Mathematical Model of Human Walking,' Lectures on Mathematics in life science, 14, Amer. Math. Soc., New York, 1981