Neural network parallel force/position control of robot manipulators under environment and robot dynamics uncertainties

• Autorzy: Ferguene F. , Achour N. , Toumi R.
• Języki publikacji: EN

Abstrakty

EN

The performance of a parallel force/position controller for robot force tracking is affected by the uncertainties in both the robot dynamics and the environment stiffness. This paper aims to improve the controller's robustness by applying the neural network (NN) technique to compensate for the robot dynamics at the input trajectory level and adaptive feed-forward compensation to cope with variations in the contact environment. A NN control technique is applied to a conventional PID force/position parallel control scheme which is composed of a PD action on position loop and a proposed adaptive I (integral) action on the force loop, which allows a complete use of available sensor measurements by operating the control action in a full dimensional space without using selection matrices. Simulation results for a three degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of a full dynamic robot and large environment stiffness uncertainties.

Słowa kluczowe

EN

force/position control; parallel control; PID control; neural network controllers; adaptive control; robot manipulators

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2009
• Tom: Vol. 19, no. 1
• Strony: 93--121
• Opis fizyczny: Bibliogr. 31 poz., rys.

Twórcy

autor

Ferguene F.

autor

Achour N.

autor

Toumi R.

• LRPE, Faculty of Electronics and Computer Science, Algeria,

Bibliografia

• [1] B. ARMSTRONG and O. KHATIB: Explicit dynamie model and inertial parameters of PUMA 560 arm. Proc. IEEE Int. Conf. on Robotics and Automation, San Francisco, USA, (1986), 510-518.
• [2] S. C. CHIAN and Y. L. KUANG: Robust adaptive motion/force tracking design for uncertain constrained robot manipulators. Automatica, 40 (2004), 2111-2119.
• [3] S. CHIAVERINI and L. SCIAVESCO: The parallel approach to force/position con-trol of robotic manipulator. IEEE J. Trans, on Robotics and Automation. 9(4), (1993), 361-373.
• [4] S. CHIAVERINI and B. SICILIANO: Force/position regulation of compliant robot manipulators. IEEE J. Trans, on Automation and Control. 39(3), (1994), 647-652.
• [5] S. CHIAVERINI and B. SICILIANO: A stable force/position controller for robot manipulators. Proc. IEEE Int. Conf. on Decision and Control, (1992), 1869-1874.
• [6] E. DEGOULANGE: Commande en effort d’un robot manipulateur a deux bras: Application au controle d'une chaine cinematiaue fermee. These de Doctorat, Universite Montpellier II, France, 1993.
• [7] E. DEGOULANGE and P. DAUCHEZE: Force control of a industrial PUMA 560 robot under environmental constraints: implementation issues and experimental re-sults. Proc. IEEE Conf. on Robotics and Automation, Atlanta, USA, (1993), 213-218.
• [8] R. DUMAS and C. SAMSON: Robust nonlinear control of robotic manipulators: implementation aspect and simulation. Int. Report Inria, Rennes, France. 1987.
• [9] F. FERGUENE and R. TOUMI: A neural approach to force/position parallel control of robotic manipulators application to the follow-up of trajectory in unknown envi-ronment stiffness. Proc. Int. Computer Systems and Information Technology Conf, 1 (2005), 247-251.
• 40] S. HAYKIN: Neural networks: A comprehensive foundation. Prentice Hall 2nd edition. 1999.
• [11] N. R. HOGAN: Impedance control: An approach to manipulator: parts I, II and III. ASMEJ. Dynam. Syst., Meas., Contr., 10 (1985), 1-24.
• [12] N. R. HOGAN: Stable execution of contact tasks using impedance control. Proc. IEEE Conf. Robotics and Automation, Raleigh, (1987), 1047-1054.
• [13] S. JUNG and T. C. HSIA: Neural network impedance force control of robot manipulator. IEEEJ. Trans, on Industrial Electronics. 45(3), (1998), 451-461.
• [14] S. JUNG and T. C. HSIA: Robust neural force control design under uncertainties in robot dynamics and unknown environment. IEEE J. Trans, on Industrial Electronics. 47(2), (2000), 403-412.
• [15] S. JUNG and T. C. HSIA: Experimental studies of neural network impedance forces control for robot manipulators. Proc. IEEE Int. Conf Robotics and Automation. (2001),3453-3458.
• [16] S. JUNG and T. C. HSIA: New neural network control technique for non model based robot manipulators control. Proc. IEEE Int. Conf. on Robotics and Automation, (1995), 2928-2933.
• [17] S. JUNG and T. C. HSIA: A new neural network eon troi technique for robot manipulator. Proc. American Control Conf., (1995), 878-882.
• [18] S. JUNG and T. C. HSIA: On reference trajectory modincation approach for cartesian space neural network control of robot manipulators. Proc. IEEE Int. Conf. Robotics and Automation, (1995), 575-580.
• [19] S. JUNG and T. C. HSIA: Force tracking impedance control of robot manipulators under unknown environment. IEEE Trans. On Control Systems Technology. 12(3), (2004), 474-483.
• [20] O. KHATIB and J. BURDICK: Motion and force control of robot manipulators. Proc. IEEE Int. Conf. Robotics and Automation, San Francisco, USA, (1986), 1381-1386.
• [21] O. KHATIB: A Unified approach for motion and force control of robot manipulators: the operational space formulation. IEEE J. Robotics and Automation, RA-3(1), (1987), 43-53.
• [22] K. NAKAWONO and M. KATAGIRI: Force and position control of robot manipulator using neurocontroller with GA based training. Proc. IEEE Int. Symp. on Computational Intelligence in Robotics and Automation, (2003), 1354-1357.
• [23] S. J. MARQUES and L. BAPTISTA: Force control of robot manipulators with neural networks compensation: A comparative study. Proc. IEEE ISIE, (1997), 872-876.
• [24] J. MILLS and A. GOLDENBERG: Forces and position control of manipulators during constrained motion task. IEEE J. Trans, on Robotics and Automation, 5(1), (1989), 30-46.
• [25] V. PERDEREAU: Contribution a la commande hybride force-position application a la cooperation de deux robots. These de Doctorat Universite Pierre et Marie Curie, France, 1991.
• [26] M. H. RAIBERT and J.J. CRAIG: Hybrid position/force control of manipulator. ASMEJ. Dynam. Syst. Meas. Contr., 102 (1981), 126-133.
• [27] T. YOSHIKAWA: Force control of robot manipulators. Proc. IEEE Int. Conf. Robotics and Automation, (2000), 220-226.
• [28] K. T. SONG and H.P. Li: Design and experiment of fuzzy force controller for an industrial robot. Proc. Natl. Sci. Counc. Roc(A), 19(1), (1995), 26-36.
• [29] S. K. SlNGH and D.O. POPA: An analysis of some fundamental problems in adap-tive control of force and impedance behavior: Theory and experiments. IEEE Trans, on Robotics and Automation, 11 (1995), 912-921.
• [30] L. L. WHITCOMB: Adaptive model-based hybrid control of geometrically con-strained robot Arms. IEEE Trans, on Roboties and Automat Urn. 13(1), (1997), 105-116.
• [31] B. YAO and S. P. CHAN: Robust motion and force control of robot manipulators in the presence of environmental constraint uncertainties. In Proc. IEEE Conf. on Decision and Control, (1992), 1875-1880.