Abstract
Tracking control of closed-chain robotic manipulators has posed a challenging and difficult task due to the complicated dynamic model, the presence of multi closed-loop chains and singularities. This paper presents a novel tracking controller using radial basic function networks (RBFNs) for closed-chain robotic manipulators. The dynamic model of a general closed-chain robotic manipulator is presented in the presence of structured and unstructured uncertainties. In order to compensate the uncertainties, the RBFNs are used. An adaptation law is proposed to adjust on-line the output weights of the RBFNs. The validity of the proposed controller is shown by computer simulations of a five-bar planar parallel manipulator.
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References
Ghorbel, F.H., et al.: Modeling and Set Point Control of Closed-chain Mechanisms: Theory and Experiment. IEEE Transactions on Control Systems Technology 8 (2000)
Abdellatif, H., Heimann, B.: Advanced Model-Based Control of a 6-DOF Hexapod Robot: A Case Study. IEEE/ASME Transactions on Mechatronics 15 (2010)
Ouyang, P.R., et al.: Nonlinear PD Control for Trajectory Tracking with Consideration of the Design for Control Methodology. In: Proceedings IEEE International Conference on Robotics and Automation, ICRA 2002, vol. 4, pp. 4126–4131 (2002)
Lu, R., et al.: Trajectory Tracking Control for a 3-DOF Planar Parallel Manipulator Using the Convex Synchronized Control Method. IEEE Transactions on Control Systems Technology 16, 613–623 (2008)
Paccot, F., et al.: A Vision-based Computed Torque Control for Parallel Kinematic Machines. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 1556–1561 (2008)
Shang, W.W., et al.: Dynamic Model based Nonlinear Tracking Control of a Planar Parallel Manipulator. Nonlinear Dynamics 60, 597–606 (2010)
Shang, W., Cong, S.: Nonlinear Adaptive Task Space Control for a 2-DOF Redundantly Actuated Parallel Manipulator. Nonlinear Dynamics 59, 61–72 (2010)
Hunt, K.J., et al.: Extending the Functional Equivalence of Radial Basis Function Networks and Fuzzy Inference Systems. IEEE Transactions on Neural Networks 7 (1996)
Jung, L.M., Kiu, C.Y.: An Adaptive Neurocontroller Using RBFN for Robot Manipulators. IEEE Transactions on Industrial Electronics 51, 711–717 (2004)
Shuzhi, S.G., et al.: Adaptive Neural Network Control of Robot Manipulators in Task Space. IEEE Transactions on Industrial Electronics 44, 746–752 (1997)
Sun, F.C., et al.: Neural Adaptive Tracking Controller for Robot Manipulators with Unknown Dynamics. In: IEE Proceedings-Control Theory and Applications, vol. 147 (2000)
Hui, C., et al.: Dynamics and Control of Redundantly Actuated Parallel Manipulators. IEEE/ASME Transactions on Mechatronics 8, 483–491 (2003)
Slotine, J.J.E., Li, W.: Applied Nonliner Control. Prentice-Hall (1991)
Tien, D.L., et al.: Robot manipulator modeling in Matlab-SimMechanics with PD control and online gravity compensation. In: 2010 International Forum on Strategic Technology (IFOST), pp. 446–449 (2010)
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© 2012 Springer-Verlag Berlin Heidelberg
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Le, T.D., Kang, HJ., Suh, YS. (2012). A Tracking Controller Using RBFNs for Closed-Chain Robotic Manipulators. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_62
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DOI: https://doi.org/10.1007/978-3-642-31837-5_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31836-8
Online ISBN: 978-3-642-31837-5
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