Abstract
This paper investigates vision based robot control based on a receding horizon control strategy. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from an energy function of the visual feedback system. By applying the proposed control scheme to a two-link direct drive manipulator with a CCD camera, it is shown that the stabilizing receding horizon control nicely works for a planar visual feedback system. Furthermore, actual nonlinear experimental results are assessed with respect to the stability and the performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
S. Hutchinson, G.D. Hager and P.I. Corke (1996). A tutorial on visual servo control. IEEE Trans. Robotics and Automation. 12(5):651–670.
R. Kelly (1996). Robust asymptotically stable visual servoing of planar robots. IEEE Trans. Robotics and Automation. 12(5):759–766.
A. Maruyama and M. Fujita (1998). Robust control for planar manipulators with image feature parameter potential. Advanced Robotics. 12(l):67–80.
H. Kawai and M. Fujita (2004). Passivity-based dynamic visual feedback control for three dimensional target tracking: stability and L2-gain performance analysis. Proc. 2004 American Control Conference. 1522–1527.
D.Q. Mayne, J.B. Rawlings, C.V. Rao and P.O.M. Scokaert (2000). Constrained model predictive control: stability and optimality. Automatica. 36(6): 789–814.
T. Parisini and R. Zoppoli (1995). A receding-horizon regulator for nonlinear systems and a neural approximation. Automatica. 31(10):1443–1451.
A. Jadbabaie, J. Yu and J. Häuser (2001). Unconstrained receding-horizon control of nonlinear systems. IEEE Trans. Automatic Control. 46(5):776–783.
J. Yu, A. Jadbabaie, J. Primbs and Y. Huang (2001). Comparison of nonlinear control design techniques on a model of the caltech ducted fan. Automatica. 37(12):1971–1978.
A. Jadbabaie and J. Häuser (2002). Control of a thrust-vectored flying wing: a receding horizon—LPV approach. International Journal of Robust and Nonlinear Control. 12(9):869–896.
A.E. Hunt and A.C. Sanderson (1982). Vision-based predictive robotic tracking of a moving target. Technical Report. Carnegie Mellon University.
M.W. Spong, S. Hutchinson and M. Vidyasagar (2006). Robot modeling and control. John Wiley & Sons.
M. Fujita, A. Maruyama, M. Watanabe and H. Kawai (2000). Inverse optimal H∞ disturbance attenuation for planar manipulators with the eye-in-hand system. Proc. 39th IEEE Conference on Decision and Control. 3945–3950.
T. Ohtsuka (2004). A continuation/GMRES method for fast computation of nonlinear receding horizon control. Automatica. 40(4):563–574.
J.B. Rawlings (2000). Tutorial overview of model predictive control. IEEE Control Systems Magazine. 20(3):38–52.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Fujita, M., Murao, T., Kawai, Y., Nakaso, Y. (2007). An Experimental Study of Stabilizing Receding Horizon Control of Visual Feedback System with Planar Manipulators. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_48
Download citation
DOI: https://doi.org/10.1007/978-3-540-72699-9_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72698-2
Online ISBN: 978-3-540-72699-9
eBook Packages: EngineeringEngineering (R0)