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Adaptive impedance controller design for flexible-joint electrically-driven robots without computation of the regressor matrix

Published online by Cambridge University Press:  11 May 2011

Ming-Chih Chien  and
An-Chyau Huang
Ming-Chih Chien
Affiliation:
Mechanical and Systems Research Laboratories, Industrial Technology Research Institute, No. 195, Sec. 4, Chung-Hsing Rd., Chutung, Hsinchu 31040, Taiwan, R.O.C.
An-Chyau Huang*
Affiliation:
Department of Mechanical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Rd., Sec. 4, Taipei 10607, Taiwan, R.O.C.
*
*Corresponding author. E-mail: [email protected]
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Summary

To the best of our knowledge, this is the first paper focus on the adaptive impedance control of robot manipulators with consideration of joint flexibility and actuator dynamics. Controller design for this problem is difficult because each joint of the robot has to be described by a fifth-order cascade differential equation. In this paper, a backstepping-like procedure incorporating the model reference adaptive control strategy is employed to construct the impedance controller. The function approximation technique is applied to estimate time-varying uncertainties in the system dynamics. The proposed control law is free from the calculation of the tedious regressor matrix, which is a significant simplification in implementation. Closed-loop stability and boundedness of internal signals are proved by the Lyapunov-like analysis with consideration of the function approximation error. Computer simulation results are presented to demonstrate the usefulness of the proposed scheme.

Keywords

Adaptive impedance controlFlexible-joint electrically driven robotFAT
Type
Articles
Information
Robotica , Volume 30 , Issue 1 , January 2012 , pp. 133 - 144
Copyright
Copyright © Cambridge University Press 2011

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References

1.Hogan, N., “Impedance control: An approach to manipulator: Part I-III,” ASME J. Dyn. Syst. Meas. Control 107, 1–24 (1985).CrossRefGoogle Scholar
2.Anderson, R. J. and Spong, M. W., “Hybrid impedance control of robotic manipulators,” IEEE Trans. Robot. Autom. 4, 549–556 (1988).CrossRefGoogle Scholar
3.Gonzalez, J. J. and Widmann, G. R., “A force commanded impedance control scheme for robots with hard nonlinearities,” IEEE Trans. Control Syst. Technol. 3 (4), 398–408 (1995).CrossRefGoogle Scholar
4.Yoshikawa, T., “Force Control of Robot Manipulators,” Proceedings of the IEEE Conference on Robotics and Automation, San Francisco, USA (2000) pp. 220–226.Google Scholar
5.Park, J. H., “Impedance control for biped robot locomotion,” IEEE Trans. Robot. Autom. 17 (6), 870–882 (2001).CrossRefGoogle Scholar
6.Jung, S., Hsia, T. C. and Bonitz, R. G., “Force tracking impedance control of robot manipulators under unknown environment,” IEEE Trans. Control Syst. Technol. 12 (3), 474–483 (2004).CrossRefGoogle Scholar
7.Huang, L., Ge, S. S. and Lee, T. H., “Neural network adaptive impedance control of constrained robots,” Int. J. Robot. Autom. 19 (3), 117–124 (2004).Google Scholar
8.Good, M. C., Sweet, L. M. and Strobel, K. L., “Dynamic model for control system design of integrated robot and drive systems,” ASME J. Dyn. Syst. Meas. Control 107, 53–59 (1985).CrossRefGoogle Scholar
9.Tarn, T. J., Bejczy, A. K., Yun, X. and Li, Z., “Effect of motor dynamics on nonlinear feedback robot arm control,” IEEE Trans. Robot. Autom. 7 (1), 114–122 (1991).CrossRefGoogle Scholar
10.Spong, M. W., “On the force control problem for flexible-joint manipulators,” IEEE Trans. Autom. Control 34, 107–111 (1989).CrossRefGoogle Scholar
11.Eppinger, S. D. and Seering, W. P., “Three dynamic problem in robot force control,” IEEE Trans. Robot. Autom. 8, 751–758 (1992).CrossRefGoogle Scholar
12.Krishnan, H., “Control of constrained robots including effects of joint flexibility and actuator dynamics,” Int. J. Robust Nonlinear Control 5 (4), 303–312 (1995).CrossRefGoogle Scholar
13.Krishnan, H., “Design of force/position control laws for constrained robots, including effects of joint flexibility and actuator dynamics,” Robotica 17, 41–48 (1999).CrossRefGoogle Scholar
14.Kwan, C. W., “Hybrid force/position control for manipulators with motor dynamics using a sliding-adaptive approach,” IEEE Trans. Autom. Control 40 (5), 963–968 (1995).CrossRefGoogle Scholar
15.Kwan, C. W., “Robust adaptive force/motion control of constrained robots,” IEE Proc. Control Theor. Appl. 143 (1), 103–109 (1996).CrossRefGoogle Scholar
16.Colbaugh, R., Glass, K. and Wedeward, K., “Adaptive Compliance Control of Electrically-Driven Manipulators,” Proceedings of the IEEE Conference on Decision and Control, Kobe, Japan (1996) pp. 394–399.CrossRefGoogle Scholar
17.de Queiroz, M. S., Dawson, D. M. and Canbolat, H., “Adaptive Position/Force Control of BDC-RLED Robots without Velocity Measurements,” Proceedings of the IEEE International Conference on Robotics and Automation, Albuquerque, NM, USA, (1997) pp. 525–530.CrossRefGoogle Scholar
18.Chang, Y.-C. and Lee, C.-H., “Robust tracking control for constrained robots actuated by DC motors without velocity measurements,” IEE Proc. Control Theor. Appl. 146 (2), 147–156 (1999).CrossRefGoogle Scholar
19.Wai, R. J. and Yang, Z. W., “Adaptive fuzzy neural network control design via a T-S fuzzy model for a robot manipulator including actuator dynamics,” IEEE Trans. Syst. Man Cybern. Part B: Cybern. 38, 1326–1346 (2008).Google Scholar
20.Jafarian, H., Eghtesad, M. and Tavasoli, A., “Combined adaptive-robust and neural network control of two RLED cooperating robots using backstepping design,” Int. J. Robot. Autom. 23, 106–116 (2008).Google Scholar
21.Li, Z., Ge, S. S., Adams, M. and Wijesoma, W. S., “Adaptive robust output-feedback motion/force control of electrically driven nonholonomic mobile manipulators,” IEEE Trans. Control Syst. Technol. 16, 1308–1315 (2008).Google Scholar
22.Deghat, M., Khayatian, A. R. and Eghtesad, M., “Experimental Study of a Robust-Adaptive Controller Design for Two Cooperating RLED Robot Manipulators Carrying a Rigid Payload,” Proceedings of the IEEE International Conference on Mechatronics, Malaga, Spain (2009) pp. 1–6.Google Scholar
23.Lian, K. Y., Jean, J. H. and Fu, L. C., “Adaptive force control of single-link mechanism with joint flexibility,” IEEE Trans. Robot. Autom. 7, 540–545 (1991).CrossRefGoogle Scholar
24.Lin, T. and Goldenberg, A. A., “A unified Approach to Motion and Force Control of Flexible Joint Robots,” Proceedings of the IEEE International Conference on Robotics and Automation, Minneapolis, Minnesota, (1996) pp. 1115–1120.Google Scholar
25.Lin, T. and Goldenberg, A. A., “On Coordinated Control of Multiple Flexible-Joint Robots Holding a Constrained Object,” Proceedings of the IEEE Internatinal Conference on Robotics and Automation, Albuquerque, New Mexico, (1997) pp. 1490–1495.Google Scholar
26.Colbaugh, R., Glass, K. and Gallegos, G., “Adaptive Compliant Motion Control of Flexible-Joint Manipulators,” Proceedings of the IEEE International Conference on American Control, Albuquerque, New Mexico, (1997) pp. 1873–1878.Google Scholar
27.Hu, Y. R. and Vukovich, G., “Position and force control of flexible-joint robots during constrained motion tasks,” Mech. Mach. Theory 36, 853–871 (2001).CrossRefGoogle Scholar
28.Tian, L., Wang, J. and Mao, Z., “Constrained motion control of flexible robot manipulators based on recurrent neural networks,” IEEE. Trans. Syst. Man Cybern. Part B: Cybern. 34 (3), 1541–1552 (2004).CrossRefGoogle ScholarPubMed
29.Faroog, M., Wang, D. B. and Dar, N. U., “Hybrid force/position control scheme for flexible joint robot with friction between and the end-effector and the environment,” Int. J. Eng. Sci. 46, 1266–1278 (2008).Google Scholar
30.Huang, J. B., Xie, Z. W., Liu, H. and Sun, K., “Adaptive Cartesian impedance control system for flexible joint robot by using DSP/FPGA architecture,” Int. J. Robot. Autom. 23, 251–258 (2008).Google Scholar
31.Chaoui, H., Sicard, P. and Gueaieb, W., “ANN-based adaptive control of robotic manipulators with friction and joint elasticity,” IEEE Trans. Ind. Electron. 56, 3174–3187 (2009).CrossRefGoogle Scholar
32.Huang, A. C. and Kuo, Y. S., “Sliding control of nonlinear systems containing time-varying uncertainties with unknown bounds,” Int. J. Control 74, 252–264 (2001).CrossRefGoogle Scholar
33.Ge, S. S., Hang, C. C., Lee, T. H. and Zang, T., Stable Adaptive Neural Network Control (Kluwer Academic, Boston, 2001).Google Scholar
34.Spooner, J. T., Maggiore, M., Ordonez, R. and Passino, K. M., Stable Adaptive Control and Estimation for Nonlinear Systems – Neural and Fuzzy Approximator Techniques (John Wiley & Sons, NY, USA, 2002).Google Scholar
35.Chien, M. C. and Huang, A. C., “Adaptive impedance control of robot manipulators based on function approximation technique,” Robotica 22, 395–403 (2004).CrossRefGoogle Scholar
36.Huang, A. C. and Chen, Y. C., “Adaptive multiple-surface sliding control for non-autonomous systems with mismatched uncertainties,” Automatica 11, 1939–1945 (2004).CrossRefGoogle Scholar
37.Huang, A. C. and Chen, Y. C., “Adaptive sliding control for single-link flexible-joint robot with mismatched uncertainties,” IEEE Trans. Control Syst. Technol. 12, 770–775 (2004).CrossRefGoogle Scholar
38.Chen, P. C. and Huang, A. C., “Adaptive sliding control of non-autonomous active suspension systems with time-vary loadings,” J. Sound Vib. 282, 1119–1135 (2005).CrossRefGoogle Scholar
39.Chen, P. C. and Huang, A. C., “Adaptive multiple-surface sliding control of non-autonomous active suspension systems based on function approximation technique,” J. Vib. Control 11, 685–706 (2005).CrossRefGoogle Scholar
40.Chen, P. C. and Huang, A. C., “Adaptive sliding control of active suspension systems with uncertain hydraulic actuator dynamics,” Veh. Sys. Dyn. 44 (5), 357–368 (2006).CrossRefGoogle Scholar
41.Huang, A. C., Wu, S. C. and Ting, W. F., “An FAT-based adaptive controller for robot manipulators without regressor matrix: Theory and experiments,” Robotica 24, 205–210 (2006).CrossRefGoogle Scholar
42.Huang, A. C. and Liao, K. K., “FAT-based adaptive sliding control for flexible arms, theory and experiments,” J. Sound Vibration 298, 194–205 (2006).CrossRefGoogle Scholar
43.Chien, M. C. and Huang, A. C., “Adaptive control of flexible-joint electrically-driven robot with time-varying uncertainties,” IEEE Trans. Ind. Electron. 54 (2), 1032–1038 (2007).CrossRefGoogle Scholar
44.Chien, M. C. and Huang, A. C., “Adaptive control of electrically-driven robot without computation of regressor matrix,” J. Chin. Inst. Eng. 30 (5), 855–862 (2007).CrossRefGoogle Scholar
45.Chien, M. C. and Huang, A. C., “FAT-Based Adaptive Visual Servoing for Robots with Time Varying Uncertainties,” Proceedings of the IEEE International Conference on Robotics and Automation, Kobe, Japan (2009), pp. 3700–3705.Google Scholar
46.Huang, A. C. and Chien, M. C., “Design of a Regressor-Free Adaptive Impedance Controller for Flexible-Joint Electrically-Driven Robots,” Proceedings of the IEEE International Conference Industrial Electronics and Applications, Xi'an, China (2009), pp. 17–22.Google Scholar
47.Slotine, J-J. E. and Li, W., “On the adaptive control of robotic manipulators” Int. J. Robot. Res. 6 (3), 49–59 (1987).CrossRefGoogle Scholar
48.Ortega, R. and Spong, M. W., “Adaptive motion control of rigid robots: A tutorial,” Automatica 25, 877–888 (1989).CrossRefGoogle Scholar
49.Spong, M. W., “Modeling and control of elastic joint robots,” ASME J. Dyn. Syst. Meas. Control 109, 310–319 (1987).CrossRefGoogle Scholar
50.Lin, T. and Goldenberg, A. A., “Robust Adaptive Control of Flexible Joint Robots with Joint Torque Feedback,” Proceedings of the IEEE Conference on Robotics and Automation, Nagoya, Japan (1995) pp. 1229–1234.Google Scholar
51.Narendra, K. S. and Annaswamy, A. M., Stable Adaptive System (Prentice Hall, NJ, USA, 1989).Google Scholar
52.Slotine, J-J. E. and Li, W., Applied Nonlinear Control (Prentice Hall, NJ, USA, 1991).Google Scholar
53.Khalil, H. K., Nonlinear Systems (Prentice-Hall, NJ, USA, 2002).Google Scholar
54.Spong, M. W. and Vidyasagar, M., Robot Dynamics and Control (John Wiley & Sons, NY, USA, 1989).Google Scholar