Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-24T09:50:48.283Z Has data issue: false hasContentIssue false
  • English
  • Français

Polynomial-Based Robust Adaptive Impedance Control of Electrically Driven Robots

Published online by Cambridge University Press:  04 November 2020

Alireza Izadbakhsh Open the ORCID record for Alireza Izadbakhsh [Opens in a new window]  and
Saeed Khorashadizadeh Open the ORCID record for Saeed Khorashadizadeh [Opens in a new window]
Alireza Izadbakhsh*
Affiliation:
Department of Electrical Engineering, Garmsar branch, Islamic Azad University, Garmsar, Iran
Saeed Khorashadizadeh
Affiliation:
Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran
*
*Corresponding author. E-mail: izadbakhsh_alireza@hotmail.com
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents a robust adaptive impedance controller for electrically driven robots using polynomials of degree N as a universal approximator. According to the universal approximation theorem, polynomials of degree N can approximate uncertainties including un-modeled dynamics and external disturbances. This fact is completely discussed and proved in this paper. The polynomial coefficients are estimated based on the adaptive law calculated in the stability analysis. A performance evaluation has been carried out to verify satisfactory performance of the controller. Simulation results on a two degree of freedom manipulator have been presented to guarantee its successful implementation.

Keywords

Impedance controlRobot manipulatorFunction approximation techniqueRobust adaptive controlUniversal approximation theorem
Type
Article
Information
Robotica , Volume 39 , Issue 7 , July 2021 , pp. 1181 - 1201
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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

Carloni, R., Sanfelice, R. G., Teel, A. R. and Melchiorri, C., “A Hybrid Control Strategy for Robust Contact Detection and Force Regulation,” American Control Conference ACC 2007, New York, NY, USA (2007) pp. 1461–1466.Google Scholar
Craig, J. J. and Raibert, M. H., “A Systematic Method of Hybrid Position/Force Control of a Manipulator,” Proceedings of the Computer Software and Applications and the IEEE Computer Society’s Third International Conference, COMPSAC 1979, Chicago, IL, USA (1979) pp. 446–451.Google Scholar
Fanaei, A. and Farrokhi, M., “Robust adaptive neuro-fuzzy controller for hybrid position/force control of robot manipulators in contact with unknown environment,” J. Intell. Fuzzy Syst. 17(2), 125–144 (2006).Google Scholar
Chien, M.-C. and Huang, A. C., “Regressor-Free Adaptive Impedance Control of Flexible-Joint Robots Using FAT,” In: American Control Conference, Minneapolis, MN, USA (2006) pp. 3904–3909, doi: 10.1109/ACC.2006.1657328.CrossRefGoogle Scholar
Gonzalez, J. J. and Widmann, G. R., “A force commanded impedance control scheme for robots with hard nonlinearities,” IEEE Trans. Syst, Control. Technol. 3(4), 398–408 (1995).Google Scholar
Chan, S., Yao, B., Gao, W. and Cheng, M., “Robust impedance control of robot manipulators,” Int. J. Robot. Automat. 6(4), 220–227 (1991).Google Scholar
Bickel, R., Tomizuka, M. and Chung, W., “Hybrid Impedance Control in Constraint Coordinates Using a Disturbance Observer,” Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, Japan (1996) pp. 1974–1979.Google Scholar
Jafari, A., Monfaredi, R., Rezaei, M., Talebi, A. and Ghidary, S. S., “Sliding Mode Hybrid Impedance Control of Robot Manipulators Interacting With Unknown Environments Using VSMRC Method,” In: ASME 2012 International Mechanical Engineering Congress and Exposition, Houston, Texas, USA (2012) pp. 1071–1081.Google Scholar
Anderson, R. and Spong, M. W., “Hybrid impedance control of robotic manipulators,” IEEE J. Robot. Automat. 4, 549–556 (1988).CrossRefGoogle Scholar
Ahmadi, S. M. and Fateh, M. M., “Task-space control of robots using an adaptive Taylor series uncertainty estimator,” Int. J. Control 92(9), 2159–2169 (2018). doi: 10.1080/00207179.2018.1429673.CrossRefGoogle Scholar
Izadbakhsh, A., Khorashadizadeh, S. and Kheirkhahan, P., “Real-time fuzzy fractional-order control of electrically driven flexible-joint robots,” AUT J. Model. Simulat. (2018), doi: 10.22060/MISCJ.2018.13523.5075 CrossRefGoogle Scholar
Chaoui, H., W. Gueaieb M. Biglarbegian and M. C. Yagoub, “Computationally efficient adaptive type-2 fuzzy control of flexible-jointanipulators,” Robotics 2(2), 66–91 (2013).CrossRefGoogle Scholar
Izadbakhsh, A. and Kheirkhahan, P., “An alternative stability proof for ‘adaptive type-2 fuzzy estimation of uncertainties in the control of electrically flexible-joint robots’,” J. Vibr. Control 25(5), 977–983 (2019).CrossRefGoogle Scholar
Izadbakhsh, A., Khorashadizadeh, S. and Ghandali, S., “Robust adaptive impedance control of robot manipulators using Szasz-Mirakyan operator as universal approximator,” ISA Trans. doi: 10.1016/j.isatra.2020.06.017 CrossRefGoogle Scholar
Izadbakhsh, A. and Khorashadizadeh, S., “Robust impedance control of robot manipulators using differential equations as universal approximator,” Int. J. Control 91(10), 2170–2186 (2018).CrossRefGoogle Scholar
Izadbakhsh, A., Khorashadizadeh, S. and Kheirkhahan, P., “Tracking control of electrically driven robots using a model free observer,” Robotica 37(4), 729–755 (2019).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., “Robust adaptive control of voltage saturated flexible joint robots with experimental evaluations,” AUT J. Model. Simul. 50(1) (2017). doi: 10.1016/10.22060/miscj.2017.12174.5008 CrossRefGoogle Scholar
Izadbakhsh, A., Jabbari Asl, H. and Narikiyo, T., “Robust Adaptive Control of Over-Constrained Actuated Cable-Driven Parallel Robots,” In: Cable-Driven Parallel Robots, CableCon 2019, Mechanisms and Machine Science (Pott, A. and Bruckmann, T., eds.), vol. 74 (Springer, Cham, 2019), pp. 209–220. doi: 10.1007/978-3-030-20751-9_18 CrossRefGoogle Scholar
Chien, M. C. and Huang, A. C., “Adaptive impedance control of robot manipulators based on function approximation technique,” Robotica 22(4), 395–403 (2004).CrossRefGoogle Scholar
Izadbakhsh, A. and Kheirkhahan, P., “Adaptive fractional-order control of electrical flexible-joint robots: Theory and experiment,” Proc. Inst. Mech. Eng. I J. Syst. Control Eng. 233(9), 1136–1145 (2019).Google Scholar
Izadbakhsh, A. and Masoumi, M., “FAT-Based Robust Adaptive Control of Flexible-Joint Robots: Singular Perturbation Approach,” In: Annual IEEE Industrial Society’s 18th International Conference on Industrial Technology, Toronto, ON, CA (2017) pp. 803–808, doi: 10.1109/ICIT.2017.7915462.CrossRefGoogle Scholar
Izadbakhsh, A. and Khorashadizadeh, S., “Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator,” Int. J. Robust Nonlinear Control 30(7), 2719–2735 (2020).CrossRefGoogle 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(2), 205–210 (2006).CrossRefGoogle Scholar
Izadbakhsh, A. and Kheirkhahan, P., “A note on the ‘task-space control of robots using an adaptive Taylor series uncertainty estimator’,” Int. J. Control (2019). doi: 10.1080/00207179.2019.1614674 CrossRefGoogle Scholar
Izadbakhsh, A. and Kheirkhahan, P., “On the voltage-based control of robot manipulators revisited,” Int. J. Control Automat. Syst. 16(4), 1887–1894 (2018).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
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
Huang, A. C. and Chen, M. C., Adaptive Control of Robot Manipulators: A Unified Regressor-Free Approach (World Scientific Publishing Co. Pte. Ltd., Singapore, 2010).CrossRefGoogle Scholar
Izadbakhsh, A., Kheirkhahan, P. and Khorashadizadeh, S., “FAT-based robust adaptive control of electrically driven robots in interaction with environment,” Robotica 37(5), 779–800 (2019).CrossRefGoogle Scholar
Izadbakhsh, A. and Khorashadizadeh, S., “Single-loop PID controller design for electrical flexible-joint robots,” J. Braz. Soc. Mech. Sci. Eng. 42(2), 1–12 (2010).Google Scholar
Qu, Z. and Dawson, D. M., Robust Tracking Control of Robot Manipulators (IEEE Press, Inc., New York, 1996).Google Scholar
Izadbakhsh, A. and Rafiei, S. M. R., “Endpoint perfect tracking control of robots – A robust non inversion-based approach,” Int. J. Control Automat. Syst. 7(6), 888–898 (2009).CrossRefGoogle Scholar