Browse > Article
http://dx.doi.org/10.5391/IJFIS.2014.14.1.17

Neural Network Compensation for Impedance Force Controlled Robot Manipulators  

Jung, Seul (The Intelligent Systems and Emotional Engineering Laboratory, Department of Mechatronics Engineering, Chungnam National University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.14, no.1, 2014 , pp. 17-25 More about this Journal
Abstract
This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.
Keywords
Neural network; Impedance control; Robot manipulator;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 D. M. Kim, H. J. Choi, J. S. Kim, W. K. Lee, D. H. Song, and S. Jung, "Tracking control of a moving object for robokers with stereo visual feedback," in IEEE International Conference on Integration Technology, Shenzhen, China, March 20-24, 2007, pp. 52-57. http://dx.doi.org/10.1109/ICITECHNOLOGY.2007.4290363   DOI
2 N. Hogan, "Impedance control: an approach to manipulation. Part ITheory," Journal of Dynamic Systems, Measurement, and Control, vol. 107, no. 1, pp. 1-7, Mar. 1985. http://dx.doi.org/10.1115/1.3140702   DOI
3 N. Hogan, "Impedance control: an approach to manipulation. Part IIImplementation," Journal of Dynamic Systems, Measurement, and Control, vol. 107, no. 1, pp. 8-16, Mar. 1985. http://dx.doi.org/10.1115/1.3140713   DOI
4 N. Hogan, "Impedance control: an approach to manipulation. Part IIIApplications," Journal of Dynamic Systems, Measurement, and Control, vol. 107, no. 1, pp. 17-24, Mar. 1985. http://dx.doi.org/10.1115/1.3140701   DOI
5 M. H. Raibert and J. J. Craig, "Hybrid position/force control of manipulators," Journal of Dynamic Systems, Measurement, and Control, vol. 103, no. 2, pp. 126-133, Jun. 1981. http://dx.doi.org/10.1115/1.3139652   DOI
6 S. Jung and T. C. Hsia, "Adaptive force tracking impedance control of robot for cutting nonhomogeneous workpiece," in Proceedings of the IEEE International Conference on Robotics and Automation, Detroit, MI, May 10-15, 1999, pp. 1800-1805. http://dx.doi.org/10.1109/ROBOT.1999.770370   DOI
7 R. Anderson and M. W. Spong, "Hybrid impedance control of robotic manipulators," in Proceedings of the IEEE International Conference on Robotics and Automation, Raleigh, NC, March 31-April 3, 1987, pp. 1073-1080. http://dx.doi.org/10.1109/ROBOT.1987.1087919   DOI
8 G. J. Liu and A. A. Goldenberg, "Robust hybrid impedance control of robot manipulators," in Proceedings of the IEEE International Conference on Robotics and Automation, Sacramento, CA, April 9-11, 1991, pp. 287-292. http://dx.doi.org/10.1109/ROBOT.1991.131589   DOI
9 S. Jung, T. C. Hsia, and R. G. Bonitz, "Force tracking impedance control of robot manipulators under unknown environment," IEEE Transactions on Control Systems Technology, vol. 12, no. 3, pp. 474-483, May. 2004. http://dx.doi.org/10.1109/TCST.2004.824320   DOI   ScienceOn
10 H. Seraji, "Adaptive admittance control: an approach to explicit force control in compliant motion," in Proceedingsof the IEEE International Conference on Robotics and Automation, San Diego, CA, May 8-13, 1994, pp. 2705-2712. http://dx.doi.org/10.1109/ROBOT.1994.350927   DOI
11 S. Jung, S. B. Yim, and T. C. Hsia, "Experimental studies of neural network impedance force control for robot manipulators," in Proceedings of the IEEE International Conference on Robotics and Automation, Seoul, Korea, May 21-26, 2001, pp. 3453-3458. http://dx.doi.org/10.1109/ROBOT.2001.933152   DOI
12 M. Dapper, R. Maass, V. Zahn, and R. Eckmiller, "Neural force control (NFC) applied to industrial manipulators in interaction with moving rigid objects," in Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium, May 16-20, 1998, pp. 2048-2053. http://dx.doi.org/10.1109/ROBOT.1998.680618   DOI
13 S. Jung and T. C. Hsia, "Robust neural force control scheme under uncertainties in robot dynamics and unknown environment," IEEE Transactions on Industrial Electronics, vol. 47, no. 2, pp. 403-412, Apr. 2000. http://dx.doi.org/10.1109/41.836356   DOI   ScienceOn
14 S. Hu, V. M. H. Ang, and H. Krishnan, "NN controller of the constrained robot under unknown constraint," in 26th Annual Conference of the IEEE Industrial Electronics Society, Nagoya, Japan, October 22-28, 2000, pp. 2123-2128. http://dx.doi.org/10.1109/IECON.2000.972604   DOI
15 M. C. Hwang and X. Hu, "A robust position/force learning controller of manipulators via nonlinear Hinfinity control and neural networks," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 30, no. 2, pp. 310-321, Apr. 2000. http://dx.doi.org/10.1109/3477.836379   DOI   ScienceOn
16 V. Mallapragada, D. Erol, and N. Sarkar, "A new method of force control for unknown environments," in IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, October 9-15, 2006, pp. 4509-4514. http://dx.doi.org/10.1109/IROS.2006.282089   DOI
17 Y. Zhao and C. C. Cheah, "Position and force control of robot manipulators using neural networks," in IEEE Conference on Robotics, Automation and Mechatronics, Singapore, December 1-3, 2004, pp. 300-305. http://dx. doi.org/10.1109/RAMECH.2004.1438935   DOI
18 F. Passold and M. R. Stemmer, "Force control of a Scara robot using neural networks," in Proceedings of the Fourth International Workshop on Robot Motion and Control, Puszczykowo, Poland, June 17-20, 2004, pp. 247-252. http://dx.doi.org/10.1109/ROMOCO.2004.240735
19 K. Kiguchi and T. Fukuda, "Intelligent position/force controller for industrial robot manipulators-application of fuzzy neural networks," IEEE Transactions on Industrial Electronics, vol. 44, no. 6, pp. 753-761, Dec. 1997. http://dx.doi.org/10.1109/41.649935   DOI   ScienceOn
20 K. Kiguchi, K. Watanabe, K. Izumi, and T. Fukuda, "Application of multiple fuzzy-neuro force controllers in an unknown environment using genetic algorithms," in Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, CA, April 24-28, 2000, pp. 2106-2111. http://dx.doi.org/10.1109/ROBOT.2000.846340   DOI
21 G. H. Lee and S. Jung, "Neuro-fuzzy control of inverted pendulum system for intelligent control education," International Journal of Fuzzy Logic and Intelligent Systems, vol. 9, no. 4, pp. 309-314, Dec. 2009.   DOI   ScienceOn
22 D. H. Song, G. H. Lee, and S. Jung, "Neural network compensation technique for standard PD-like fuzzy controlled nonlinear systems," International Journal of Fuzzy Logic and Intelligent Systems, vol. 8, no. 1, pp. 68-74, Mar. 2008.   DOI   ScienceOn
23 H. T. Cho, S. S. Kim, and S. Jung, "Experimental studies of real-time decentralized neural network control for an x-y table robot," International Journal of Fuzzy Logic and Intelligent Systems, vol. 8, no. 3, pp. 185-191, Sep. 2008.   DOI   ScienceOn
24 H. W. Kim and S. Jung, "Fuzzy logic application to a two-wheel mobile robot for balancing control performance," International Journal of Fuzzy Logic and Intelligent Systems, vol. 12, no. 2, pp. 154-161, Jun. 2012. http://dx.doi.org/10.5391/IJFIS.2012.12.2.154   과학기술학회마을   DOI   ScienceOn
25 S. Jung and H. T. Cho, "Decoupled neural network reference compensation technique for a PD controlled two degrees-of-freedom inverted pendulum," International Journal of Control Automation and System, vol. 2, no. 1, pp. 92-99, Mar. 2004.   과학기술학회마을
26 S. Jung and T. C. Hsia, "Neural network inverse control techniques for PD controlled robot manipulator," Robotica, vol. 18, no. 3, pp. 305-314, May. 2000. http://dx.doi.org/10.1017/S0263574799002064   DOI   ScienceOn