Abstract
Hydraulically actuated robotic mechanisms are becoming popular for field robotic applications for their compact design and large output power. However, they exhibit nonlinearity, parameter variation and flattery delay in the response. This flattery delay, which often causes poor trajectory tracking performance of the robot, is possibly caused by the dead zone of the proportional electromagnetic control valves and the delay associated with oil flow. In this investigation, we have proposed a trajectory tracking control system for hydraulically actuated robotic mechanism that diminishes the flattery delay in the output response. The proposed controller consists of a robust adaptive fuzzy controller with self-tuned adaptation gain in the feedback loop to cope with the parameter variation and disturbances and a one-step-ahead fuzzy controller in the feed-forward loop for hydraulic dead zone pre-compensation. The adaptation law of the feedback controller has been designed by Lyapunov synthesis method and its adaptation rate is varied by fuzzy self-tuning. The variable adaptation rate helps to improve the tracking performance without sacrificing the stability. The proposed control technique has been applied for locomotion control of a hydraulically actuated hexapod robot under independent joint control framework. For tracking performance of the proposed controller has also been compared with classical PID controller, LQG state feedback controller and static fuzzy controller. The experimental results exhibit a very accurate foot trajectory tracking with very small tracking error with the proposed controller.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Wang, L.X., Mendel, J.M.: Fuzzy basis functions, universal approximation, and orthogonal least-square learning. IEEE Trans. Neural Netw. 3(5), 807–814 (1992)
Park, J.H., Seo, S.J., Park, G.T.: Robust adaptive fuzzy controller for nonlinear system using estimation of bounds for approximation Errors. Fuzzy Sets Syst. 133, 19–36 (2003)
Wang, L.X.: Stable adaptive fuzzy control of nonlinear systems. IEEE Trans. Fuzzy Syst. l1(2), 146–155 (1993)
Chen, B.S., Lee, C.H., Chang, Y.C.: H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans. Fuzzy Syst. 4(1), 32–43 (1996)
Fischle, K., Schröder, D.: An improved stable adaptive fuzzy control method. IEEE Trans. Fuzzy Syst. 7(1), 27–40 (1999)
Ge, S.S., Wang, J.: Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems. IEEE Trans. Neural Netw. 13(6), 1409–1419 (2002)
Kim, Y.T., Bien, Z.Z.: Robust adaptive fuzzy control in the presence of external disturbance and approximation error. Fuzzy Sets Syst. 148, 377–393 (2004)
Bu, F., Yao, B.: Nonlinear model based coordinated adaptive robust control of electro-hydraulic arms via overparameterizing method. In: Proc. IEEE International Conf. on Robotics and Automation 2001, pp. 3459–3464 (2001)
Corbet, T., Sepehri, N., Lawrence, P.D.: Fuzzy control of a class of hydraulically actuated industrial robot. IEEE Trans. Control Syst. Technol. 4, 419–426, (1996)
Wang, X.S., Su, C.Y., Hong, H.: Robust adaptive control of a class of nonlinear systems with unknown dead-zone. In: Proc. of 40th IEEE Conf. on Decision and Control, pp. 1627–1632 (2001)
Nonami, K., Ikedo, Y.: Walking control of COMET-III using discrete time preview sliding mode control. In: Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 2004, pp. 3219–3225 (2004)
Mudi, R.K., Pal, N.R.: A self-tuning fuzzy PI-controller. Fuzzy Sets Syst. 115, 327–338 (2000)
Nonami, K., Huang, Q., Komizo, D., Fukao, Y., Asai, Y., Shiraishi, Y., Fujimoto, M., Ikedo, Y.: Development and control of mine detection robot COMET-II and COMET-III. JSME Int. J. Ser. C. 46(3), 881–890 (2003)
Spong, M.W., Vidyasagar, M.: Robot Dynamics and Control. Wiley, New York, NY (1989)
Driankov, D., Hellendoorn, H., Reinfrank, M.: An introduction to fuzzy control. Springer, Berlin (1996)
Ioannou, P.A., Sung, J.: Robust Adaptive Control, p. 07458. Prentice Hall, Upper Saddle River, NJ (1996)
Ioannou, P.A.: Robust adaptive control: a unified approach. Proc. IEEE. 79(12), 1736–1767 (1991)
Johnson, C.R.: Adaptive implementation of one-step-ahead optimal control via input matching. IEEE Trans. Automat. Contr. AC-23, 865–872 (1978)
Tanaka, K., Sugeno, M.: Stability and design of fuzzy control systems. Fuzzy Sets Syst. 45, 135–156 (1992)
Slotine, J., Li, W.: Applied Nonlinear Control. Prentice Hall, Englewood Cliffs, NJ (1991)
Wang, H.O., Tanaka, K.: An approach to fuzzy control of nonlinear: systems stability and design issues. IEEE Trans. Fuzzy Syst. 4(1), 14–23 (1996)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Barai, R.K., Nonami, K. Locomotion Control of a Hydraulically Actuated Hexapod Robot by Robust Adaptive Fuzzy Control with Self-Tuned Adaptation Gain and Dead Zone Fuzzy Pre-compensation. J Intell Robot Syst 53, 35–56 (2008). https://doi.org/10.1007/s10846-008-9231-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-008-9231-8