Main Article Content

Maximilian Jaderson De Melo
Federal Institute of Education, Science and Technology of Mato Grosso do Sul - campus Naviraí
Brazil
Biography
Mauricio Begnini
Federal Institute of Education, Science and Technology of Santa Catarina
Brazil
Heber Rabelo Da Silva
Federal Institute of Education, Science and Technology of Santa Catarina
Brazil
Marcelo Christiano Da França Júnior
Brazil
Vol. 7 No. 2 (2018), Articles, pages 27-42
DOI: https://doi.org/10.14201/ADCAIJ2018722742
Accepted: Sep 13, 2018
Copyright

Abstract

This paper addresses the robust formation control of non-holonomic mobile robots with homogeneous system architecture and decentralized control structure. Therefore, it was necessary the mathematical modeling of mobile robots, from which, the Separation-Bearing variant of Leader-Following control strategy was implemented. The stability proof were based on the Lyapunov theory. The sliding mode control (SMC) strategy was used in the controller design to make the control robust to the incidence of uncertainties and disturbances. The Fuzzy Adaptive Formation Control is designed to eliminate the  previous bounding knowledge of these uncertainties and disturbances. The proposed control effectiveness is demonstrated by results obtained with simulations in Matlab/Simulink. The pure kinematic and kinematic with disturbances is also analyzed. The results shows the controllers effectiveness to formation of multi-robots systems to the eight-shaped trajectory.

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References

Begnini, M., Bertol, D. W., and Martins, N. A., 2015. VALIDATION OF A SIMPLE AND EFFECTIVE ROBUST ADAPTIVE FUZZY VARIABLE STRUCTURE TRACKING CONTROL FOR THE WHEELED

MOBILE ROBOT. International Journal of Innovative Computing, Information and Control.

Chatraei, A. and Javidian, H., 2015. Formation control of mobile robots with obstacle avoidance using fuzzy artificial potential field. In Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), 2015 IEEE International Workshop of, pages 1–6. doi:10.1109/ECMSM.2015.7208710.

Chen, Y.-Q. and Wang, Z., 2005. Formation control: a review and a new consideration. In Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on, pages 3181–3186. doi: 10.1109/IROS.2005.1545539.

Corradini, M. L., Leo, T., and Orlando, G., 1999. Robust stabilization of a mobile robot violating the nonholonomic constraint via quasi-sliding modes. In Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), volume 6, pages 3935–3939 vol.6. ISSN 0743-1619. doi:10.1109/ACC.1999.786255.

DeCarlo, R. A., Zak, S. H., and Matthews, G. P., 1988. Variable structure control of nonlinear multivariable systems: a tutorial. Proceedings of the IEEE, 76(3):212–232.

Dierks, T. and Jagannathan, S., 2007. Control of Nonholonomic Mobile Robot Formations: Backstepping Kinematics into Dynamics. In Control Applications, 2007. CCA 2007. IEEE International Conference on, pages 94–99. doi:10.1109/CCA.2007.4389212.

Dierks, T. and Jagannathan, S., 2009. Neural Network Control of Mobile Robot Formations Using RISE Feedback. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(2):332–347. ISSN 1083-4419. doi:10.1109/TSMCB.2008.2005122.

Dixon, W., Dawson, D., and Zergeroglu, E., 2000. Tracking and regulation control of a mobile robot system with kinematic disturbances: A variable structure-like approach. Journal of Dynamic Systems, Measurement, and Control, 122(4):616–623.

Fierro, R. and Lewis, F., 1995. Control of a nonholonomic mobile robot: backstepping kinematics into dynamics. In Decision and Control, 1995., Proceedings of the 34th IEEE Conference on, volume 4, pages 3805–3810 vol.4. ISSN 0191-2216. doi:10.1109/CDC.1995.479190.

Kamel, M. A. and Zhang, Y., 2015. Decentralized leader-follower formation control with obstacle avoidance of multiple unicycle mobile robots. In 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), pages 406–411. ISSN 0840-7789. doi:10.1109/CCECE.2015.7129312.

Kanayama, Y., Kimura, Y., Miyazaki, F., and Noguchi, T., 1990. A stable tracking control method for an autonomous mobile robot. In Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on, pages 384–389 vol.1. doi:10.1109/ROBOT.1990.126006.

Kanayama, Y., Kimura, Y., Miyazaki, F., and Noguchi, T., 1991. A stable tracking control method for a non-holonomic mobile robot. In Intelligent Robots and Systems ’91. ’Intelligence for Mechanical Systems, Proceedings IROS ’91. IEEE/RSJ International Workshop on, pages 1236–1241 vol.3. doi:10.1109/IROS. 1991.174669.

Kanjanawanishkul, K., 2005. Formation control of mobile robots: survey. eng. ubu. ac. th, pages 50–64.

Kowdiki, K. H., Barai, R. K., and Bhattacharya, S., 2012. Leader-follower formation control using artificial potential functions: A kinematic approach. In IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012), pages 500–505.

Liu, J. and Wang, X., 2011. Advanced Sliding Mode Control for Mechanical Systems. Springer-Verlag Berlin Heidelberg, 1 edition.

Martins, N. A., Elyoussef, E. S., Bertol, D. W., Pieri, E. R. D., Moreno, U. F., and d. B. Castelan, E., 2011. Trajectory Tracking of a Nonholonomic Mobile Robot with Kinematic Disturbances: A Variable Structure Control Design. IEEE Latin America Transactions, 9(3):276–283. ISSN 1548-0992. doi:10.1109/TLA.2011. 5893772.

Mastellone, S., Stipanovic’, D. M., Graunke, C. R., Intlekofer, K. A., and Spong, M. W., 2008. Formation Control and Collision Avoidance for Multi-agent Non-holonomic Systems: Theory and Experiments. The International Journal of Robotics Research, 27(1):107–126. doi:10.1177/0278364907084441.

Raimúndez, C. and Paz, E., 2013. Adaptive mobile robots formation control using neural networks. In 2013 European Control Conference (ECC), pages 884–889.

Shaw, I. and Simões, M., 1999. Controle e modelagem fuzzy. Edgard Blucher. ISBN 9788521202486.

Utkin, V. and Shi, J., 1996. Integral sliding mode in systems operating under uncertainty conditions. In Decision and Control, 1996., Proceedings of the 35th IEEE Conference on, volume 4, pages 4591–4596 vol.4. ISSN 0191-2216. doi:10.1109/CDC.1996.577594.

Utkin, V. I., 1992. Sliding modes in control and optimization, volume 116. Springer-Verlag Berlin.

Wang, J., Rad, A., and Chan, P., 2001. Indirect adaptive fuzzy sliding mode control: Part I: fuzzy switching. Fuzzy Sets and Systems, 122(1):21 – 30. ISSN 0165-0114. doi:http://dx.doi.org/10.1016/S0165-0114(99)00179-7.

Yan-dong, L., Ling, Z., and Ming, S., 2013. Adaptive RBFNN Formation Control of Multi-mobile Robots with Actuator Dynamics. Indonesian Journal of Electrical Engineering and Computer Science, 11(4):1797–1806.