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Locomotion control of a hydraulically actuated hexapod robot by robust adaptive fuzzy control and dead-zone compensation

Published online by Cambridge University Press:  01 May 2006

Ranjit Kumar Barai  and
Kenzo Nonami
Ranjit Kumar Barai*
Affiliation:
Graduate School of Science and Technology, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 2638522, Japan.
Kenzo Nonami
Affiliation:
Department of Electronics and Mechanical Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 2638522, Japan.
*
*Corresponding author. E-mail: ranjit@graduate.chiba-u.jp
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Summary

This investigation presents locomotion control of a hydraulically actuated six-legged humanitarian demining robot by robust adaptive fuzzy control in conjunction with the dead zone compensation technique within independent joint control framework. For proper locomotion of the demining robot, accurate tracking of the desired joint trajectory is very important. However, high degree of nonlinearity, the uncertainties due to changing hydraulic properties, and delay due to the flow of oil and dead zone of the proportional electromagnetic control valve results into an inaccurate plant model for the hydraulically actuated robotic joints. Consequently, model-based classical control techniques result into a large tracking error. Therefore, adaptive fuzzy control technique, being a model independent control paradigm for complex and uncertain systems, is a good choice for such systems. In this work, a hydraulic dead zone compensated robust adaptive fuzzy control law has been proposed for locomotion control of hydraulically actuated hexapod demining robot. The experimental results exhibit a fairly accurate trajectory tracking of the leg joints and, consequently, very stable locomotion of the walking robot.

Keywords

Robust adaptive fuzzy control (RAFC)Hydraulic actuatorSix-legged walking robotRobot locomotion
Type
Article
Information
Robotica , Volume 25 , Issue 3 , May 2006 , pp. 269 - 281
Copyright
Copyright © Cambridge University Press 2006

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References

1.Ioannou, P. A., “Robust adaptive control: A unified approach,” Proc. IEEE 79 (12), 1736–1767 1991.CrossRefGoogle Scholar
2.Wang, L. X., “Stable adaptive fuzzy control of nonlinear systems,” IEEE Trans. Fuzzy Syst. 1 (2), 146–155 1993.CrossRefGoogle Scholar
3.Chen, B. S., Lee, C. H. and Chang, Y. C., “H∞ tracking design of uncertain nonlinear SISO systems: Adaptive fuzzy approach,” IEEE Trans. Fuzzy Syst. 4 (1), 32–43 1996.CrossRefGoogle Scholar
4.Park, J. H., Seo, S. J. and Park, G. T., “Robust adaptive fuzzy controller for nonlinear system using estimation of bounds for approximation errors,” Fuzzy Sets Syst. 133, 19–36 2003.CrossRefGoogle Scholar
5.Bu, F. and Yao, B., “Nonlinear model based coordinated adaptive robust control of electro-hydraulic arms via overparameterizing method,” Proceedings of the IEEE International Conference on Robotics and Automation 2001 pp. 3459–3464.Google Scholar
6.Wang, L. X. and Mendel, J. M., “Fuzzy basis functions, universal approximation, and orthogonal least-square learning,” IEEE Trans. Neural Netw. 3 (5), 807–814 1992.CrossRefGoogle Scholar
7.Mudi, R. K. and Pal, N. R., “A self-tuning fuzzy PI-controller,” Fuzzy Sets Syst. 115, 327–338 2000.CrossRefGoogle Scholar
8.Nonami, K., Huang, Q., Komizo, D., Fukao, Y., Asai, Y., Shiraishi, Y., Fujimoto, M. and Ikedo, Y., “Development and control of mine detection robot COMET-II and COMET-III,” JSME Int. J. Ser. C 46 (3), 881–890 2003.CrossRefGoogle Scholar
9.Driankov, D., Hellendoorn, H. and Reinfrank, M., An Introduction to Fuzzy Control (Springer-Verlag, Berlin, Germany, 1996).CrossRefGoogle Scholar
10.Fischle, K. and Schröder, D., “An improved stable adaptive fuzzy control method,” IEEE Trans. Fuzzy Syst. 7 (1), 27–40 1999.CrossRefGoogle Scholar
11.Ge, S. S. and Wang, J., “Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems,” IEEE Trans. Neural Netw. 13 (6), 1409–1419 2002.CrossRefGoogle ScholarPubMed
12.Kim, Y. T. and Bien, Z. Z., “Robust adaptive fuzzy control in the presence of external disturbance and approximation error,” Fuzzy Sets Syst. 148, 377–393 2004.CrossRefGoogle Scholar
13.Corbet, T., Sepehri, N. and Lawrence, P. D., “Fuzzy control of a class of hydraulically actuated industrial robots,” IEEE Trans. Control Syst. Technol. 4 (4), 419–426 1996.CrossRefGoogle Scholar
14.Wang, H. O. and Tanaka, K., “An approach to fuzzy control of nonlinear systems: Stability and design issues,” IEEE Trans. Fuzzy Syst. 4 (1), 14–23 1996.CrossRefGoogle Scholar
15.Tanaka, K. and Sugeno, M., “Stability and design of fuzzy control systems,” Fuzzy Sets Syst. 45, 135–156 1992.CrossRefGoogle Scholar
16.Spong, M. W. and Vidyasagar, M., Robot Dynamics and Control (Wiley, New York, NY, 1989).Google Scholar
17.Ioannou, P. A. and Sung, J., Robust Adaptive Control (Prentice-Hall, Upper Saddle River, NJ, 1996).Google Scholar
18.Nonami, K. and Ikedo, Y., “Walking control of COMET-III using discrete time preview sliding mode control,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 2004 pp. 3219–3225.Google Scholar
19.Corbet, T., Sepehri, N. and Lawrence, P. D., “Fuzzy control of a class of hydraulically actuated industrial robot,” IEEE Trans. Control Syst. Technol. 4 (4), 419–426 1996.CrossRefGoogle Scholar
20.Wang, X. S., Su, C. Y. and Hong, H., “Robust adaptive control of a class of nonlinear systems with unknown dead-zone,” Proceedings of the 40th IEEE Conference on Decision and Control 2001 pp. 1627–1632.Google Scholar
21.Johnson, C. R., “Adaptive implementation of one-step-ahead optimal control via input matching,” IEEE Trans. Autom. ControlAC-23, 865–872 1978.CrossRefGoogle Scholar
22.Slotine, J. and Li, W., Applied Nonlinear Control (Prentice-Hall, Englewood Cliffs, NJ, 1991).Google Scholar