Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-24T12:30:15.474Z Has data issue: false hasContentIssue false
  • English
  • Français

FAT-Based Robust Adaptive Control of Electrically Driven Robots in Interaction with Environment

Published online by Cambridge University Press:  18 December 2018

Alireza Izadbakhsh Open the ORCID record for Alireza Izadbakhsh [Opens in a new window] ,
Payam Kheirkhahan Open the ORCID record for Payam Kheirkhahan [Opens in a new window]  and
Saeed Khorashadizadeh
Alireza Izadbakhsh*
Affiliation:
Department of Electrical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran E-mail: [email protected]
Payam Kheirkhahan
Affiliation:
Department of Electrical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran E-mail: [email protected]
Saeed Khorashadizadeh
Affiliation:
Faculty of Electrical and Computer Engineering, University of Birjand, 615/97175 Birjand, Iran E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents a robust adaptive impedance controller for robot manipulators using function approximation techniques (FAT). Recently, FAT-based robust impedance controllers have been presented using Fourier series expansion for uncertainty estimation. In fact, sinusoidal functions can approximate nonlinear functions with arbitrary small approximation error based on the orthogonal functions theorem. The novelty of this paper in comparison with previous related works is that the number of required regressor matrices in this paper has been reduced. This superiority becomes more dominant when the manipulator degrees of freedom (DOFs) are increased. First, the desired signals for motor currents are calculated, and then the desired voltages are obtained. In the proposed approach, only a simple model of the actuator and manipulator dynamics is used in the controller design and all the rest dynamics are treated as external disturbance. The external disturbances can then be approximated by Fourier series expansion. The adaptation laws for Fourier series coefficients are derived from a Lyapunov-based stability analysis. Simulation results on a 2-DOF planar robot manipulator including the actuator dynamics indicate the efficiency of proposed method.

Keywords

Impedance controlRobot manipulatorFunction approximation techniqueRobust adaptive control
Type
Articles
Information
Robotica , Volume 37 , Issue 5 , May 2019 , pp. 779 - 800
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Mao, Y. and Agrawal, S. K., “Design of a cable-driven arm exoskeleton (CAREX) for neural rehabilitation,” IEEE Trans. Robot. 28, 922–931 (2012).CrossRefGoogle Scholar
Spong, M. W., Lewis, F. L. and Abdallah, C. T., Robot Control: Dynamics, Motion Planning, and Analysis (IEEE Press, New York, 1993).Google Scholar
Whitney, D. E., “Historical perspective and state of the art in robot force control,” Int. J. Robot. Res. 6, 3–14 (1987).CrossRefGoogle Scholar
Hogan, N., “Impedance control: An approach to manipulation: Part I-III,” ASME J. Dyn. Syst. Meas. Control 107, 1–24 (1985).CrossRefGoogle Scholar
Kazerooni, H., “On the robot compliant motion control,” ASME J. Dyn. Syst. Meas. Control 111, 416–425 (1989).CrossRefGoogle Scholar
Raibert, M. and Craig, J., “Hybrid position/force control of manipulators,” ASME J. Dyn. Syst. Meas. Control 102, 126–133 (1981).CrossRefGoogle Scholar
Khatib, O., “A unified approach for motion and force control of robot manipulators: The operational space formulation,” IEEE J. Robot. Autom. 3, 43–53 (1987).CrossRefGoogle Scholar
Almeida, F., Lopes, A. and Abreu, P., “Force-impedance control: A new control strategy of robotic manipulators,” Recent Adv. Mechatr. 126–137 (1999).Google Scholar
Kazerooni, H., Houpt, P. and Sheridan, T., “Robust compliant motion for manipulators: Part II, design method,” IEEE J. Robot. Autom. 2, 93–105 (1986).CrossRefGoogle Scholar
Seraji, H. and Colbaugh, R., “Force tracking in impedance control,” Int. J. Robot. Res. 16, 97–117 (1997).CrossRefGoogle Scholar
Boaventura, T., Buchli, J., Semini, C. and Caldwell, D. G., “Model-based hydraulic impedance control for dynamic robots,” IEEE Trans. Robot. 31, 1324–1336 (2015).CrossRefGoogle Scholar
Filaretov, V. F. and Zuev, A. V., “Adaptive Force/Position Control of Robot Manipulators,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Xian, China (2008) pp. 96–101.CrossRefGoogle Scholar
Spong, M. W., Hutchinson, S. and Vidyasagar, M., Robot Modelling and Control (Wiley, Hoboken, 2006).Google Scholar
Slotine, J. J. E. and Li, W., “Adaptive Strategies in Constrained Manipulation,” Proceedings of IEEE International Conference on Robotics and Automation, Raleigh, NC, USA, 4 (1987) pp. 595–601.Google Scholar
Colbaugh, R., Seraji, H. and Glass, K., “Direct Aadaptive Impedance Control of Manipulators.” Proceedings of IEEE Conference on Decision and Control, Brighton, UK, 3 (1991) pp. 2410–2415.Google Scholar
Zhen, R. R. Y. and Goldenberg, A. A., “An Adaptive Approach to Constrained Robot Motion Control,” Proceedings of IEEE International Conference on Robotics and Automation, Nagoya, Japan, 2 (1995) pp. 1833–1838.Google Scholar
Izadbakhsh, A. and Fateh, M. M., “Real-time robust adaptive control of robots subjected to actuator voltage constraint,” Nonlinear Dyn. 78, 1999–2014 (2014).CrossRefGoogle Scholar
Izadbakhsh, A. and Masoumi, M., “FAT-Based Robust Adaptive Control of Flexible-Joint Robots: Singular Perturbation Approach,” Annual IEEE Industrial Society’s 18th International Conference on Industrial Technology (ICIT), Toronto, ON, Canada (2017) pp. 803–808.Google Scholar
Izadbakhsh, A., “Robust adaptive control of voltage saturated flexible joint robots with experimental evaluations,” AUT J. Model. Sim. 50(1), 31–38 (2018).Google Scholar
Huang, A. C., Wu, S. C. and Ting, W. F., “A FAT-based adaptive controller for robot manipulators without regressor matrix: Theory and experiments,” Robotica 24, 205–210 (2006).CrossRefGoogle Scholar
Chien, M. C. and Huang, A. C., “Adaptive impedance controller design for flexible-joint electrically-driven robots without computation of the regressor matrix,” Robotica 30, 133–144 (2012).CrossRefGoogle Scholar
Izadbakhsh, A., “FAT-based robust adaptive control of electrically driven robots without velocity measurements,” Nonlinear Dyn. 89, 289–304 (2017).CrossRefGoogle Scholar
Izadbakhsh, A., “A note on the nonlinear control of electrical flexible-joint robots,” Nonlinear Dyn. 89, 2753–2767 (2017).CrossRefGoogle Scholar
Izadbakhsh, A. and Rafiei, S. M. R., “Robust Control Methodologies for Optical Micro Electro Mechanical Systems–New Approaches and Comparison,” Proceedings of the 13th International Power Electronics and Motion Control Conference (IEEE-EPE-PEMC), Poznan, Poland (2008) pp. 2102–2107.Google Scholar
Izadbakhsh, A. and Khorashadizadeh, S., “Robust task-space control of robot manipulators using differential equations for uncertainty estimation,” Robotica 35(9), 1923–1938 (2017).CrossRefGoogle Scholar
Izadbakhsh, A. and Khorashadizadeh, S., “Robust impedance control of robot manipulators using differential equations as universal approximator,” Int. J. Control 91(10), 1–17 (2017).Google Scholar
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
Huang, A. C. and Chien, M. C., Adaptive Control of Robot Manipulators: A Unified Regressor-Free Approach. (World Scientific Publishing Co. Pte. Ltd., Singapore, 2010).CrossRefGoogle Scholar
Yang, R., Yang, C., Chen, M. and Na, J. “Adaptive impedance control of robot manipulators based on Q-learning and disturbance observer,” Syst. Sci. Control Eng. 5(1), 287–300 (2017).CrossRefGoogle Scholar
Ficuciello, F., Villani, L. and Siciliano, B., “Variable impedance control of redundant manipulators for intuitive human–robot physical interaction,” IEEE Trans. Rob. 31(4), 850–863 (2015).CrossRefGoogle Scholar
Lee, J., Chang, P. H. and Jamisola, R. S., “Relative impedance control for dual-arm robots performing asymmetric bimanual tasks,” IEEE Trans. Ind. Electr. 61(7), 3786–3796 (2014).CrossRefGoogle Scholar
Fateh, M. M. and Khoshdel, V., “Voltage-based adaptive impedance force control for a lower-limb rehabilitation robot,” Adv. Robot. 29(15), 961–971 (2015).CrossRefGoogle Scholar
Fateh, M. M. and Babaghasabha, R., “Impedance control of robots using voltage control strategy,” Nonlinear Dyn. 74(1–2), 277–286 (2013).CrossRefGoogle Scholar
Khorashadizadeh, S. and Fateh, M. M., “Uncertainty estimation in robust tracking control of robot manipulators using the Fourier series expansion,” Robotica 35(2), 310–336 (2017).CrossRefGoogle Scholar
Chu, Z., Cui, J. and Sun, F., “Fuzzy adaptive disturbance-observer-based robust tracking control of electrically driven free-floating space manipulator,” IEEE Syst. J. 8(2), 343–352 (2014).CrossRefGoogle Scholar
Dawson, D. M., Qu, Z. and Carroll, J. J., “Tracking control of rigid-link electrically-driven robot manipulators,” Int. J. Control 56(5), 991–1006 (1992).CrossRefGoogle Scholar
Wang, H., Ren, W., Cheah, C. C. and Xie, Y., “Dynamic Modularity Approach to Adaptive Inner/Outer Loop Control of Robotic Systems,” 35th Chinese Control Conference, Chengdu, China (IEEE, 2016) pp. 3249–3255.Google Scholar
Izadbakhsh, A. and Fateh, M. M., “Robust Lyapunov-based control of flexible-joint robots using voltage control strategy,” Arab. J. Sci. Eng. 39, 3111–3121 (2014).CrossRefGoogle Scholar
Izadbakhsh, A. and Rafiei, S. M. R., “Endpoint perfect tracking control of robots– A robust non inversion-based approach,” Int. J. Control Autom. Syst. 7(6), 888–898 (2009).CrossRefGoogle Scholar