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Distributed adaptive control strategy for flexible link manipulators

Published online by Cambridge University Press:  01 July 2016

Fareh Raouf ,
Saad Mohamad ,
Saad Maarouf  and
Bettayeb Maamar
Fareh Raouf*
Affiliation:
Department of Electrical and Computer Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. E-mail: [email protected]
Saad Mohamad
Affiliation:
School of Engineering, Université du Québec en Abitibi-Témiscamingue, 445, boul. de l'Université, Rouyn-Noranda, Quebec J9X 5E4, Canada. E-mail: [email protected]
Saad Maarouf
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Université du Québec, 1100 Notre-Dame West, Montreal, Quebec H3C 1K3, Canada. E-mail: [email protected]
Bettayeb Maamar
Affiliation:
Department of Electrical and Computer Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper presents an adaptive distributed control strategy for n-serial-flexible-link manipulators. The proposed adaptive controller is used for flexible-link-manipulators: (1) to solve the tracking control problem in the joint space, and (2) to reduce vibrations of the links. The dynamical model of flexible link manipulators is reorganized to take the form of n interconnected subsystems. Each subsystem has a one-joint and one-link pair. The system parameters are deemed to be unknown. The adaptive distributed strategy controls one subsystem in each step, starting from the last one. The nth subsystem is controlled by assuming that the remaining subsystems are stable. Then, proceeding backward to the (n-1)th system, the same strategy is applied, and so on, until the first subsystem is reached. The gradient-based estimator is used to estimate the parameters of each subsystem. The control law of the ith subsystem uses its own estimated parameters and the estimated parameters of all upper level subsystems. The global stability of the error dynamics is proved using Lyapunov approach. This algorithm was implemented in real time on a two-flexible-link manipulator, and a comparison with the non-adaptive version shows the effectiveness of this approach.

Keywords

Distributed controlAdaptive controlFlexible-link manipulatorsError dynamicsStability
Type
Articles
Information
Robotica , Volume 35 , Issue 7 , July 2017 , pp. 1562 - 1584
Copyright
Copyright © Cambridge University Press 2016 

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References

1. Benosman, M., “Control of flexible manipulators: A survey,” Robotica 22, 533 (2004).CrossRefGoogle Scholar
2. Abe, A., “Trajectory planning for residual vibration suppression of a two-link rigid-flexible manipulator considering large deformation,” Mech. Mach. Theory 44, 1627 (2009).Google Scholar
3. Cannon, R. H. Jr and Schmitz, E., “Initial experiments on the end-point control of a flexible one-link robot,” Int. J. Robot. Res. 3, 62–75 (1984).Google Scholar
4. Vakil, M., Fotouhi, R. and Nikiforuk, P. N., “Maneuver control of the multilink flexible manipulators,” Int. J. Non-Linear Mech. 44, 831–844 (2009).Google Scholar
5. Tokhi, M. O. and Azad, A. K., Flexible robot manipulators: modelling, simulation and control vol. 68: Iet, Stevenage, UK (2008).Google Scholar
6. Khorasani, K., “Feedback linearization of a flexible manipulator near its rigid body manifold,” Syst. Control Lett. 6, 187 (1985).Google Scholar
7. Atashzar, S. F., “A robust feedback linearization approach for tracking control of flexible-link manipulators using an EKF disturbance estimator,” IEEE Int. Symp. Ind. Electron. 1791 (2010).Google Scholar
8. Becedas, J., Feliu, V. and Sira-Ramirez, H., “Control of Flexible Manipulators Affected by Non-Linear Friction Torque Based on the Generalized Proportional Integral Concept,” Proceedings of the 2007 IEEE International Symposium on Industrial Electronics, Piscataway, NJ, USA (Jun. 4–7, 2007) pp. 12–17.Google Scholar
9. Chen, Y. P., “Regulation and vibration control of an FEM-based single-link flexible arm using sliding-mode theory,” J. Vib. Control 7, 741 (2001).Google Scholar
10. Wang, D., “The Design of Terminal Sliding Controller of Two-Link Flexible Manipulators,” Proceedings of the 2007 IEEE International Conference on Control and Automation, Piscataway, NJ, USA (May 30–Jun. 1, 2007) pp. 733–737.Google Scholar
11. Wang, Y.-M., Feng, Y. and Lu, Q.-L., “High-order terminal sliding mode control of flexible manipulators based on genetic algorithm,” J. Jilin University (Eng. Technol. Edition) 39, 1563–7 (2009).Google Scholar
12. Zhang, Y., Yang, T.-W. and Sun, Z.-Q., “Neuro-sliding mode endpoint control of flexible-link manipulators,” Jiqiren/Robot 30, 404–409 + 415, 2008.Google Scholar
13. Barkana, A. G. I., “Simplified Techniques for Adaptive Control of Robots,” In: Control and Dynamic Systems - Advances in Theory and Applications, (Leondes, C. T., ed.) vol. 42, (Academic Press, New York, 1991) pp. 147–203.Google Scholar
14. Ulrich, S. and Sasiadek, J. Z., “Decentralized simple adaptive control of nonlinear systems,” Int. J. Adaptive Control Signal Process. 28, 750–763 (2014).Google Scholar
15. Jung Hua, Y., Feng, L. and Li Chen, F., “Nonlinear adaptive control for flexible-link manipulators,” IEEE Trans. Robot. Autom. 13, 140–148 (1997).Google Scholar
16. Khorrami, F., Jain, S. and Tzes, A., “Adaptive Nonlinear Control and Input Preshaping for Flexible-Link Manipulators - Control/Robotics Research Laboratory (CRRL),” Proceedings of the 1993 American Control Conference Part 3 (of 3), San Francisco, CA, USA (Jun. 2–4, 1993) pp. 2705–2709.Google Scholar
17. Fareh, R., Saad, M. R. and Saad, M., “Adaptive Control for a Single Flexible Link Manipulator using Sliding Mode Technique,” Proceedings of the 6th International Multi-Conference on Systems, Signals and Devices, Djerba, Tunisia (Mar. 23–26, 2009) pp. 1–6.Google Scholar
18. Wang, Z., Zeng, H., Ho, D. W. and Unbehauen, H., “Multiobjective control of a four-link flexible manipulator: A robust H∞ approach,” IEEE Trans. Control Syst. Technol. 10, 866–875 (2002).Google Scholar
19. Kubica, E. and Wang, D., “A Fuzzy Control Strategy for a Flexible Single Link Robot,” Proceedings of the Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on, Atlanta, GA, USA (May 2–6, 1993), IEEE, IEEE Comput. Soc. Press, Los Alamitos, CA, USA, pp. 236–241.Google Scholar
20. Agee, J. T., Bingul, Z. and Kizir, S., “Tip trajectory control of a flexible-link manipulator using an intelligent proportional integral (iPI) controller,” Trans. Inst. Meas. Control, doi: 0142331213518577 (2014).Google Scholar
21. Agee, J. T., Kizir, S. and Bingul, Z., “Intelligent proportional-integral (iPI) control of a single link flexible joint manipulator,” J. Vib. Control, doi: 1077546313510729 (2013).Google Scholar
22. Scattolini, R., “Architectures for distributed and hierarchical model predictive control–a review,” J. Process Control 19, 723–731 (2009).Google Scholar
23. Al-Ashoor, R. A. and Khorasani, K., “A decentralized indirect adaptive control for a class of two-time-scale nonlinear systems with application to flexible-joint manipulators,” IEEE Trans. Ind. Electron. 46, 1019–1029 (1999).Google Scholar
24. Bona, B. and Li, W., “Adaptive Decentralized Control of a 4-DOF Manipulator with a Flexible Arm,” Proceedings of the 1992 American Control Conference, Evanston, IL, USA (Jun. 24–26, 1992) pp. 3329–3335.Google Scholar
25. Leena, G. and Ray, G., “A set of decentralized PID controllers for an n - link robot manipulator,” Sadhana - Acad. Proceedings Eng. Sci. 37, 405–423 (2012).Google Scholar
26. Al-Shuka, H. F., Corves, B. and Zhu, W.-H., “Function approximation technique-based adaptive virtual decomposition control for a serial-chain manipulator,” Robotica 1–25 (2013).Google Scholar
27. Fareh, R., Saad, M. and Saad, M., “Workspace distributed real-time control of rigid manipulators,” J. Vib. Control 20, 535–547 (2014).Google Scholar
28. Fareh, R., Saad, M. and Saad, M., “Distributed control strategy for flexible link manipulators,” Robotica 1–19 (2013).Google Scholar
29. Fareh, R., Saad, M. and Saad, M., “Workspace trajectory tracking control for two–flexible–link manipulator through output redefinition,” Int. J. Modelling, Identif. Control 18, 119–135 (2013).Google Scholar
30. De Luca, A. and Siciliano, B., “Closed-form dynamic model of planar multilink lightweight robots,” IEEE Trans. Syst. Man Cybern. 21, 826–839 (1991).Google Scholar
31. Lee, K., Wang, Y. and Chirikjian, G. S., “O mass matrix inversion for serial manipulators and polypeptide chains using Lie derivatives,” Robotica 25, 739–750 (2007).Google Scholar
32. De Luca, A. and Siciliano, B., “Explicit Dynamic Modeling of a Planar Two-Link Flexible Manipulator,” Proceedings of the 29th IEEE Conference on Decision and Control (Cat. No.90CH2917-3), New York, NY, USA (Dec. 5–7, 1990) pp. 528–30.Google Scholar
33. Craig, J. J., Introduction to Robotics: Mechanics and Control, 3rd ed. (Pearson/Prentice Hall, Upper Saddle River, N.J., 2005).Google Scholar
34. Slotine, J. J. E. and Li, W., Applied Nonlinear Control. (Prentice-Hall, Englewood Cliffs, N.J., 1991).Google Scholar
35. Barkana, I., “Defending the beauty of the invariance principle,” Int. J. Control 87, 186–206 (2014).CrossRefGoogle Scholar
36. Barkana, I., “The new theorem of stability-Direct extension of Lyapunov theorem,” Math. Eng., Sci. Aerospace (MESA) 6, 519–550 (2015).Google Scholar
37. LaSalle, J. P., “The Stability of Dynamical Systems,” vol. 25: SIAM, Philadelphia, United States (1976).Google Scholar