Nearly optimal neural network stabilization of bipedal standing using genetic algorithm

Engineering Applications of Artificial Intelligence

Volumn 20, Issue 4, 2007, Pages 473-480

  Ghorbani, Reza ^a   Wu, Qiong ^a   Wang, G Gary ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Bipedal standing; Genetic algorithm; Lyapunov exponents; Neural network; Optimal control; Postural stability

Indexed keywords

COMPUTER SIMULATION; FEEDBACK CONTROL; GENETIC ALGORITHMS; ITERATIVE METHODS; LYAPUNOV FUNCTIONS; NEURAL NETWORKS; OPTIMIZATION; PENDULUMS; REGRESSION ANALYSIS; STABILIZATION;

ENERGY-RELATED COST FUNCTION; FEEDBACK OPTIMAL CONTROLLER; GENERAL REGRESSION NEURAL NETWORK (GRNN); LYAPUNOV EXPONENTS; POSTURAL STABILITY;

BIPED LOCOMOTION;

EID: 33947157644     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2006.09.007     Document Type: Article

References (32)

1. Arakawa T., and Fukuda T. Natural motion trajectory generation of biped locomotion robot using genetic algorithm through energy optimization systems. IEEE International Conference on Man, and Cybernetics 2 (1996) 1495-1500
2. Bhat, N., Minderman, P., McAvoy Jr., T., Wang, N., 1990. Modeling chemical prosses systems via neural computation. IEEE Control Systems Magazine, 24-30.
3. Breiman, L., Meisel, W., Purcell, E., 1977. Variable kernel estimates of multivariate densities. Technometrics 19(2).
4. Brown R., Bryant P., and Abarbanel H.D.I. Computing the Lyapunov spectrum of a dynamical system from an observed time series. Physical Review A 43 (1991) 2787-2806
5. Cabodevila G., and Abba G. Quasi optimal gait for a biped robot using genetic algorithm. IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation (Cat. no. 97CH36088-5) 4 (1997) 3960-3965
6. Capi G., Kaneko S., Mitobe K., Barolli L., and Nasu Y. Optimal trajectory generation for a prismatic joint biped robot using genetic algorithms. Robotics and Autonomous Systems 38 (2002) 119-128
7. Chevallereau C., and Aoustin Y. Optimal reference trajectories foe walking and running of a biped robot. Robotica 19 (2001) 557-569
8. GAlib: Matthew's C++ Genetic Algorithms Library, lancet.mit.edu/galib-2.4/GAlib.html.
9. Goldenberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning, Reading (1989), Addison Wesley, MA
10. Grizzle J.W., Abba G., and Plestan F. Asymptotically stable walking for biped robots: analysis via systems with impulse effects. IEEE Transactions on Automatic Control 46 (2001) 46-51
11. Hemami H., and Katbab A. Constrained inverted pendulum model of evaluating upright postural stability. Journal of Dynamic Systems Measurement and Control 104 (1982) 343-349
12. Hemami H., and Stokes B.T. A qualitative discussion of mechanisms of feedback and feedforward in the control of locomotion. IEEE Transactions on Biomedical Engineering BME-30 (1983) 681-688
13. Holland J.H. Adaptation in Natural and Artificial Systems (1975), The University of Michigan Press, Ann Arbor, MI
14. Huang Q., Yokoi K., Kajita S., Kaneko Y.C., Arai H., Koyachi N., and Tanie K. Planning Walking Patterns for a Biped Robot. IEEE Transactions on Robotics and Automation 17 (2001) 280-289
15. Josin, G., Charney, D., White, D., 1988. Robot control using neural networks. In: Proceedings of the International Joint Conference Neural Networks, vol. 2, San Diego, CA, pp. 625-631.
16. Kolesnichenko O., and Shiriatev A.S. Partial stabilization of underactuated Euler-Lagrange systems via a class of feedback transformations. Systems and Control Letters 45 (2002) 121-132
17. Kuo A.D. An optimal control model for analyzing human posture balance. IEEE Transactions on Biomedical Engineering 42 (1995) 87-101
18. Kuprestien, M., Rubinstien, J., 1989. Implementation of an adaptive neural controller for sensory-motor coordination. IEEE Control Systems Magazine, 25-30.
19. Kuperstein M., and Wang J. Neural controller for addaptive movements with unforeseen payloads. IEEE Transactions on Neural Networks 1 1 (1990) 137-142
20. Nusse H.E., and Yorke J.A. Dynamics: Numerical Explorations (1998), Springer, Berlin
21. Michalewicz Z. Genetic Algorithms+ Data Structure=Evolution Programs (1996), Springer, Berlin
22. Pai Y.C., and Patton J. Center of mass velocity-position predictions for balance control. Journal of Biomechanics 30 4 (1997) 347-354
23. Pamerleau D. Efficient training of artificial neural networks for autonomous navigation. Neural Computation 3 1 (1991)
24. Plumer E. Optimal control of terminal processes using neural networks. IEEE Transactions on Neural Networks. 7 2 (1996) 408-418
25. Specht D.F. A general regression neural network. IEEE Transactions on Neural Networks 2 6 (1991) 568-576
26. Westervelt E., Grizzle J.W., and Koditschek D.E. Hybrid zero dynamics of planar biped walkers. IEEE Transactions on Automatic Control 48 1 (2003) 42-56
27. Wolf A., Swift J.B., Swinney H.L., and Vastano J.A. Determining Lyapunov exponents from a time series. Physica 16D (1985) 285-317
28. Wu Q., Sepehri N., Thornton-Trump A.B., and Alexander M. Stability and control of human trunk movement during walking. Computer Methods in Biomechanics and Biomechanical Engineering 1 (1998) 247-259
29. Wu Q., and Swain R. A mathematical model of the stability control of human thorax and pelvis movements during walking. Computer Methods in Biomechanics and Biomedical Engineering 5 (2002) 67-74
30. Yang, C., Wu, Q., 2006a. Effects of constraints on bipedal balance control. In: American Control Conference, Minneapolis, USA (accepted).
31. Yang C., and Wu Q. On stabilization of bipedal robots during disturbed standing using the concept of Lyapunov exponents. Robotica 24 (2006) 621-624
32. Zeng X., Pielke R.A., and Eykholt R. Extracting Lyapunov exponents from short time series of low precision. Modern Physics Letter B 6 (1990) 55-75