×

A computed torque controller for uncertain robotic manipulator systems: Fuzzy approach. (English) Zbl 1068.93046

Summary: Computed Torque Control (CTC) is an effective motion control strategy for robotic manipulator systems, which can ensure globally asymptotic stability. However, the CTC scheme requires precise dynamical models of robotic manipulators. To handle this impossibility, in this paper, a new approach combing CTC and Fuzzy Control (FC) is developed for trajectory tracking problems of robotic manipulators with structured uncertainty and/or unstructured uncertainty. The fuzzy part with a set of tunable parameters is employed to approximate lumped uncertainty due to parameter variations, unmodeled dynamics and so on in robotic manipulators. Based on the Lyapunov stability theorem, it is shown that the proposed controller can guarantee stability of closed-loop systems and satisfactory tracking performances. The proposed approach indicates that the CTC method is also valid for controlling uncertain robotic manipulators as long as the compensative controller is appropriately designed. Finally, computer simulation results on a two-link elbow planar robotic manipulator are presented to show tracking capability and effectiveness of the proposed scheme.

MSC:

93C85 Automated systems (robots, etc.) in control theory
93C42 Fuzzy control/observation systems
PDF BibTeX XML Cite
Full Text: DOI

References:

[1] Chan, P.T.; Rad, A.B.; Wang, J., Indirect adaptive fuzzy sliding model controlpart two: parameter projection with supervisory control, Fuzzy sets and systems, 122, 31-43, (2001) · Zbl 0981.93041
[2] Chen, B.S.; Uang, H.J.; Tseng, C.S., Robust tracking enhancement of robot systems including motor dynamics: a fuzzy-based dynamic game approach, IEEE trans. fuzzy systems, 6, 538-552, (1998)
[3] Hsu, Y.-C.; Chen, G.; Li, H.-X., A fuzzy adaptive variable structure controller with applications to robot manipulator, IEEE trans. systems man cybernet., 31, 331-340, (2001)
[4] C Hua, C.; Guan, X.; Duan, G., Variable structure adaptive fuzzy control for a class of nonlinear time delay systems, Fuzzy sets and systems, 148, 453-468, (2004) · Zbl 1056.93042
[5] Khosla, P.K.; Kanade, T., Experimental evaluation of nonlinear feedback and feedforward control schemes for manipulator, Int. J. robot. res., 7, 18-28, (1988)
[6] Kim, Y.T.; Bien, Z.Z., Robust adaptive control in the presence of external disturbance and approximation error, Fuzzy sets and systems, 148, 377-393, (2004) · Zbl 1057.93027
[7] Kim, Y.H.; Lewis, F.L., Neural network output feedback control of robot manipulators, IEEE trans. robot. automat, 15, 301-309, (1999)
[8] Labiod, S.; Boucherit, M.S.; Guerra, T.M., Adaptive fuzzy control of a class of MIMO nonlinear systems, Fuzzy sets and systems, 15, 1, 59-77, (2005), http://www.elsevier.com/locate/fss · Zbl 1142.93365
[9] Luh, J.Y.S., Conventional controller design for industrial robots-a tutorial, IEEE trans. systems man cybernet., 13, 298-316, (1983) · Zbl 0509.94001
[10] Man, Z.; Yu, X.; Ashraghian, K., A robust adaptive sliding mode tracking control using an RBF neural network for robotic manipulators, Proc. IEEE int. conf. neural networks, 5, 2403-2408, (1995)
[11] Middleton, R.H.; Goodwin, G.C., Adaptive computed torque control for rigid link manipulators, System control lett., 10, 9-16, (1988) · Zbl 0636.93051
[12] Miller, W.T.; Glanz, F.H.; Kraft, L.G., Application of a general learning algorithm to the control of robotic manipulators, Int. J. robot. res., 6, 84-98, (1987)
[13] Ozaki, T.; Suzuki, T.; Furuhashi, T.; Okuma, S.; Uchikawa, Y., Trajectory control of robotic manipulator using neural networks, IEEE trans. ind. electron., 38, 195-202, (1991)
[14] S. Purwar, I.N. Kar, A.N. Jha, Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints, Fuzzy Sets and Systems; in press. http://www.elsevier.com/locate/fss. · Zbl 1068.93045
[15] Sun, F.; Sun, Z.; Feng, G., An adaptive fuzzy controller based on sliding mode for robot manipulator, IEEE trans. systems man cybernet., 29, 661-667, (1999)
[16] Sun, F.; Sun, Z.; Woo, P.Y., Neural network-based adaptive controller design of robotic manipulators with an observer, IEEE trans. neural networks, 12, 54-67, (2001)
[17] Slotine, J.J.E.; Li, W., Adaptive manipulator controla case study, IEEE trans. automat. control, 33, 995-1003, (1988) · Zbl 0664.93045
[18] Slotine, J.J.E.; Li, W., Applied nonlinear control, (1990), Prentice-Hall International Editions New York
[19] Slotine, J.J.E.; Sastry, S.S., Tracking control of nonlinear systems using sliding surface with application to robot manipulator, Int. J. control, 38, 465-492, (1983) · Zbl 0519.93036
[20] Spong, M.W.; Vidyasagar, M., Robot dynamics and control, (1989), Wiley New York
[21] Tso, S.K.; Xu, Y.S.; Shum, H.Y., Variable structure model reference adaptive control of robot manipulators, Proc. IEEE int. conf. robot. automat., 1, 2148-2153, (1991)
[22] Wang, L.X., Stable adaptive fuzzy control of nonlinear systems, IEEE trans. fuzzy systems, 1, 146-155, (1993)
[23] Wang, J.; Rad, A.B.; Chan, P.T., Indirect adaptive fuzzy sliding model control: part one: fuzzy switching, Fuzzy sets and systems, 122, 21-30, (2001) · Zbl 0981.93040
[24] Wang, L.X.; Mendel, J.M., Fuzzy basis function universal approximation, and orthogonal least square learning, IEEE trans. neural networks, 3, 807-814, (1992)
[25] Wijesoma, S.W.; Richards, R.J., Robust trajectory following of robots using computed torque structure with VSS, Int. J. control, 52, 935-962, (1990) · Zbl 0706.70033
[26] Yi, S.Y.; Chung, M.J., A robust fuzzy logic controller for robot manipulators with uncertainties, IEEE trans. systems man cybernet., 27, 706-713, (1997)
[27] Zadeh, L., Fuzzy sets, Inform. control, 8, 338-353, (1965) · Zbl 0139.24606
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.