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Integral terminal sliding mode formation control of non-holonomic robots using leader follower approach

Published online by Cambridge University Press:  12 May 2016

Muhammad Asif*
Affiliation:
Electronic Engineering Department, Sir Syed University of Engineering and Technology, Karachi, Pakistan E-mail: muasif@ssuet.edu.pk Department of Electronics and Power Engineering, PN Engineeering College (PNEC), National University of Sciences and Technology (NUST), Islamabad, Pakistan. E-mails: junaid@pnec.nust.edu.pk, attaullah@pnec.nust.edu.pk
Muhammad Junaid Khan
Affiliation:
Department of Electronics and Power Engineering, PN Engineeering College (PNEC), National University of Sciences and Technology (NUST), Islamabad, Pakistan. E-mails: junaid@pnec.nust.edu.pk, attaullah@pnec.nust.edu.pk
Attaullah Y. Memon
Affiliation:
Department of Electronics and Power Engineering, PN Engineeering College (PNEC), National University of Sciences and Technology (NUST), Islamabad, Pakistan. E-mails: junaid@pnec.nust.edu.pk, attaullah@pnec.nust.edu.pk
*
*Corresponding author. E-mail: muasif@ssuet.edu.pk

Summary

Multi-robot formation control has become an important area of research due to its advantages and applications. This paper presents multi-robot formation control using a leader–follower approach without considering the leader's velocity information or estimation. The leader–follower formation is formulated by incorporating the model uncertainties and disturbances. A novel formation controller is presented using integral terminal sliding mode (ITSM) control, which drives the formation tracking error convergence to zero in finite-time. The stability of the close-loop control scheme is verified by using Lyapunov theory. Furthermore, obstacle detection and avoidance are incorporated to avoid collision while maintaining the formation. The effectiveness of the proposed controller is verified and validated using sine and lamniscate curve trajectories. Moreover, the performance of the proposed ITSM formation controller is compared with the standard linear sliding mode (LSM) control.

Type
Articles
Copyright
Copyright © Cambridge University Press 2016 

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References

1. Barnes, L. E., Fields, M.-A. and Valavanis, K. P., “Swarm formation control utilizing elliptical surfaces and limiting functions,” IEEE Trans. Syst. Man Cybern. Part B: Cybern. 39 (6), 61445 (2009).Google Scholar
2. Park, B. S., Yoo, S. J., Park, J. B. and Choi, Y. H., “A simple adaptive control approach for trajectory tracking of electrically driven nonholonomic mobile robots,” IEEE Trans. Control Syst. Technol. 18 (5), 51205 (2010).Google Scholar
3. Chen, Y. Q. and Wang, Z., “Formation Control: A Review and a New Consideration,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), AB, Canada, 2005, pp. 3181–3186.Google Scholar
4. Chiu, C.-S., “Derivative and integral terminal sliding mode control for a class of MIMO nonlinear systems,” Automatica 48 (2), 2326 (2012).Google Scholar
5. Choi, K., Yoo, S. J., Park, J. B. and Choi, Y. H., “Adaptive formation control in absence of leader's velocity information,” IET Control Theory Appl. 4 (4), 4528 (2010).Google Scholar
6. Consolini, L., Morbidi, F., Prattichizzo, D. and Tosques, M., “Leader-follower formation control of nonholonomic mobile robots with input constraints,” Automatica 44 (5), 51349 (2008).Google Scholar
7. Das, A. K., Fierro, R., Kumar, V., Ostrowski, J. P., Spletzer, J. and Taylor, C. J., “A vision-based formation control framework,” IEEE Trans. Robot. Autom. 18 (5), 5825 (2002).Google Scholar
8. Defoort, M., Floquet, T., Kokosy, A. and Perruquetti, W., “Sliding-mode formation control for cooperative autonomous mobile robots,” IEEE Trans. Indust. Electron. 55 (11), 113953 (2008).Google Scholar
9. Desai, J. P., Ostrowski, J. P. and Kumar, V., “Modeling and control of formations of nonholonomic mobile robots,” IEEE Trans. Robot. Autom. 17 (6), 6908 (2001).Google Scholar
10. Dierks, T. and Jagannathan, S., “Control of Nonholonomic Mobile Robot Formations: Backstepping Kinematics into Dynamics,” Proceedings of the IEEE International Conference on Control Applications, CCA 2007, Singapore, 2007, pp. 94–99.Google Scholar
11. Dierks, T. and Jagannathan, S., “Neural network output feedback control of robot formations,” IEEE Trans. Syst. Man Cybern. Part B: Cybern. 40 (2), 2399 (2010).Google Scholar
12. Drakunov, S. V. and Utkin, V. I., “Sliding mode control in dynamic systems, Int. J. Control 55 (4), 41037 (1992).Google Scholar
13. Feng, Y., Yu, X. and Han, F., “On nonsingular terminal sliding-mode control of nonlinear systems,” Automatica 49 (6), 61722 (2013).Google Scholar
14. Fredslund, J. and Mataric, M. J., “A general algorithm for robot formations using local sensing and minimal communication,” IEEE Trans. Robot. Autom 18 (5), 5846 (2002).Google Scholar
15. Ghommam, J., Mehrjerdi, H. and Saad, M., “Leader-follower Formation Control of Nonholonomic Robots with Fuzzy Logic Based Approach for Obstacle Avoidance,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, 2011, pp. 2340–2345.Google Scholar
16. Gu, D., “A differential game approach to formation control,” IEEE Trans. Control Syst. Technol. 16 (1), 193 (2008).Google Scholar
17. Guo, J., Lin, Z., Cao, M. and Yan, G., “Adaptive control schemes for mobile robot formations with triangularised structures [Brief Paper],” Control Theory Appl. IET 4 (9), 91827 (2010).Google Scholar
18. Mastellone, S., Stipanović, D. M. and Spong, M. W., “Formation control and collision avoidance for multi-agent non-holonomic systems: Theory and experiments,” Int. J. Robot. Res. 27 (1), 1126 (2008).Google Scholar
19. Mehrjerdi, H., Saad, M. and Ghommam, J., “Hierarchical fuzzy cooperative control and path following for a team of mobile robots,” IEEE/ASME Trans. Mechatronics 16 (5), 5917 (2011).CrossRefGoogle Scholar
20. Park, B. S., Park, J. B. and Choi, Y. H., “Adaptive formation control of electrically driven nonholonomic mobile robots with limited information,” IEEE Trans. Syst. Man Cybern. Part B: Cybern. 41 (4), 41075 (2011).Google Scholar
21. Poonawala, H. A., Satici, A. C. and Spong, M. W., “Leader-Follower Formation Control of Nonholonomic Wheeled Mobile Robots using Only Position Measurements,” Proceedings of the 9th Asian Control Conference (ASCC), Istanbul, 2013, pp. 1–6.Google Scholar
22. Proetzsch, M., Luksch, T. and Berns, K., “Development of complex robotic systems using the behavior-based control architecture iB2C,” Robot. Auton. Syst. 58 (1), 167 (2010).Google Scholar
23. Qi, L. and Shi, H., “Adaptive position tracking control of permanent magnet synchronous motor based on rbf fast terminal sliding mode control,” Neurocomputing 115, 2330 (2013).Google Scholar
24. Ranjbar-Sahraei, B., Shabaninia, F., Nemati, A. and Stan, S.-D., “A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems,” IEEE Trans. Indust. Electron. 59 (8), 83134 (2012).Google Scholar
25. Shen, D., Sun, W. and Sun, Z., “Adaptive pid formation control of nonholonomic robots without leader's velocity information,” ISA Trans. 53 (2), 2480 (2014).Google Scholar
26. Sun, T., Liu, F., Pei, H. and He, Y., “Brief Paper-Observer-based adaptive leader-following formation control for non-holonomic mobile robots,” Control Theory Appl. IET 6 (18), 182841 (2012).Google Scholar
27. Venkataraman, S. T. and Gulati, S., “Control of Nonlinear Systems using Terminal Sliding Modes,” American Control Conference, 1992, Chicago, IL, USA, 1992, pp. 891–893.Google Scholar
28. Zhao, D., Li, S. and Gao, F., “A new terminal sliding mode control for robotic manipulators,” Int. J. Control 82 (10), 101813 (2009).Google Scholar