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Controller design of cooperative manipulators using state-dependent Riccati equation

Published online by Cambridge University Press:  10 November 2017

Moharam Habibnejad Korayem
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology (IUST), 1684613114, Tehran, Iran. Email: hkorayem@iust.ac.ir
Saeed Rafee Nekoo*
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology (IUST), 1684613114, Tehran, Iran. Email: hkorayem@iust.ac.ir
*
*Corresponding author. E-mail: saerafee@yahoo.com

Summary

This study examined the use of a state-dependent Riccati equation (SDRE) for controller design and analysis of cooperative manipulators. The connection of end-effectors when holding an object imports constraint and complexity into the problem. Optimal load distribution (OLD) was used to divide the load between arms using a desired rate and omitting Lagrange multipliers. General dynamic structure, OLD formulation, and controller design are presented for an arbitrary number of manipulators. State-dependent coefficient parameterizations for rigid and flexible joint manipulators assuming friction for joints of them were investigated by two methods: controlling each robot independently and an entire system of robots uniformly. The effectiveness of the method, a decrease in errors, and increased stability in motion were also observed. The increase in the number of manipulators greatly expanded the state vector of the system. The SDRE was able to address this by simulation of four arms, each one possessing seven degrees of freedom (DoF). Analyses of a practical model (Scout robot) consisting of two arms with three DoF were presented and the results for connected arms and free arms were compared. The experimental data validated the simulation results and indicated that cooperation definitely improves load-carrying capacity and precision of trajectory tracking.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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References

1. Hayati, S., Tso, K. and Lee, T., “Dual arm coordination and control,” Robot. Auton. Syst. 5 (4), 333344 (1989).CrossRefGoogle Scholar
2. Kokkinis, T., “Dynamic hybrid control of cooperating robots by nonlinear inversion,” Robot. Auton. Syst. 5 (4), 359368 (1989).CrossRefGoogle Scholar
3. Li, C. J., “Coordinated motion control of multi-arm robot systems with optimal load distribution,” Syst. Control Lett. 15 (3), 237245 (1990).CrossRefGoogle Scholar
4. Yun, X., Kumar, R. V., Sarkar, N. and Paljug, E., “Control of Multiple Arm Systems with Rolling Constraints,” Technical Report, MS-CIS-91-79, 1991.Google Scholar
5. Wen, J. T. and Delgado, K. K., “Motion and force control of multiple robotic manipulators,” Automatica 28 (4), 729743 (1992).CrossRefGoogle Scholar
6. Gao, W. B. and Xiao, D., “Tracking tasks of massive objects by multiple robot systems with non-firm grasping,” Mechatronics 3 (6), 727746 (1993).CrossRefGoogle Scholar
7. Lin, S. T. and Tsai, H. C., “Impedance control with on-line neural network compensator for dual-arm robots,” J. Intell. Robot. Syst. 18 (1), 87104 (1997).CrossRefGoogle Scholar
8. Yale, G. E. and Agrawal, B. N., “Lyapunov controller for cooperative space manipulators,” J. Guid. Control Dyn. 21 (3), 477484 (1998).CrossRefGoogle Scholar
9. Liu, J. S. and Chen, S. L., “Robust hybrid control of constrained robot manipulators via decomposed equations,” J. Intell. Robot. Syst. 23 (1), 4570 (1998).CrossRefGoogle Scholar
10. Zhao, J. and Bai, S. X., “Load distribution and joint trajectory planning of coordinated manipulation for two redundant robots,” Mech. Mach. Theory 34 (8), 11551170 (1999).CrossRefGoogle Scholar
11. Jing, Z. and Bai, S. X., “The study of coordinated manipulation of two redundant robots with elastic joints,” Mech. Mach. Theory 35 (7), 895909 (2000).CrossRefGoogle Scholar
12. Ghasemi, A. and Keshmiri, M., “Performance Assessment of a Decentralized Controller for Cooperative Manipulators; Numerical and Experimental Study,” 6th International Symposium on Mechatronics and its Applications, Sharjah, United Arab Emirates (2009) pp. 1–6.Google Scholar
13. Tavasoli, A., Eghtesad, M. and Jafarian, H., “Two-time scale control and observer design for trajectory tracking of two cooperating robot manipulators moving a flexible beam,” Robot. Auton. Syst. 57 (2), 212221 (2009).CrossRefGoogle Scholar
14. Homaei, H. and Keshmiri, M., “Optimal trajectory planning for minimum vibration of flexible redundant cooperative manipulators,” Adv. Robot. 23 (12–13), 17991816 (2009).CrossRefGoogle Scholar
15. Yagiz, N., Hacioglu, Y. and Arslan, Y. Z., “Load transportation by dual arm robot using sliding mode control,” J. Mech. Sci. Technol. 24 (5), 11771184 (2010).CrossRefGoogle Scholar
16. Rastegari, R. and Moosavian, S. A. A., “Multiple impedance control of space free-flying robots via virtual linkages,” Acta Astronaut. 66 (5), 748759 (2010).CrossRefGoogle Scholar
17. Lee, S. C. and Ahn, H. S., “Multiple Manipulator Cooperative Control using Disturbance Estimator and Consensus Algorithm,” Proceedings of the IEEE American Control Conference, San Francisco, CA, USA (2011) pp. 4002–4007.Google Scholar
18. Hacioglu, Y., Arslan, Y. Z. and Yagiz, N., “MIMO fuzzy sliding mode controlled dual arm robot in load transportation,” J. Franklin Inst. 348 (8), 18861902 (2011).CrossRefGoogle Scholar
19. Panwar, V., Kumar, N., Sukavanam, N. and Borm, J. H., “Adaptive neural controller for cooperative multiple robot manipulator system manipulating a single rigid object,” Appl. Soft Comput. 12 (1), 216227 (2012).CrossRefGoogle Scholar
20. Korayem, M. H., Irani, M. and Nekoo, S. R., “Analysis of manipulators using SDRE: A closed loop nonlinear optimal control approach,” Sci. Iranica 17 (6B), 456467 (2010).Google Scholar
21. Korayem, M. H. and Nekoo, S. R., “Finite-time state-dependent riccati equation for time-varying nonaffine systems: Rigid and flexible joint manipulator control,” ISA Trans. 54, 125144 (2015).CrossRefGoogle ScholarPubMed
22. Korayem, M. H. and Nekoo, S. R., “State-dependent differential riccati equation to track control of time-varying systems with state and control nonlinearities,” ISA Trans. 57, 117135 (2015).CrossRefGoogle ScholarPubMed
23. Korayem, M. H., Esfeden, R. A. and Nekoo, S. R., “Path planning algorithm in wheeled mobile manipulators based on motion of arms,” J. Mech. Sci. Technol. 29 (4), 17531763 (2015).CrossRefGoogle Scholar
24. Korayem, M. H. and Nekoo, S. R., “The SDRE control of mobile base cooperative manipulators: Collision free path planning and moving obstacle avoidance,” Robot. Auton. Syst. 86, 86105 (2016).CrossRefGoogle Scholar
25. Schilling, R. J., Fundamentals of Robotics Analysis and Control (Prentice Hall, New Delhi, 2003).Google Scholar
26. Lian, K. Y., Hsiao, S. J. and Sung, W. T., “Intelligent multi-sensor control system based on innovative technology integration via ZigBee and wi-fi networks,” J. Netw. Comput. Appl. 36 (2), 756767 (2013).CrossRefGoogle Scholar
27. Yusoff, M. A. K., Samin, R. E. and Ibrahim, B. S. K., “Wireless mobile robotic arm,” Procedia Eng. 41, 10721078 (2012).CrossRefGoogle Scholar
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