A robust-adaptive fuzzy coverage control for robotic swarms
详细信息 查看全文
- 作者：Mostafa Jahangir (1) m.jahangir8@gmail.com
Siavash Khosravi (1) khosravi@ieee.org
Hossein Afkhami (2) hossein.afkhami@yahoo.com - 关键词：Robotic swarms – ; Robust control – ; Adaptive systems – ; Coverage control
- 刊名：Nonlinear Dynamics
- 出版年：2012
- 出版时间：August 2012
- 年：2012
- 卷：69
- 期：3
- 页码：1191-1201
- 全文大小：518.1 KB
- 参考文献：1. Roman-Ballesteros, I., Pfeiffer, C.: A framework for cooperative multi-robot surveillance tasks. In: Electronics, Robotics and Automotive Mechanics Conference, Cuernavaca, Mexico, vol. 2, pp. 163–170 (2006)
2. Schwager, M., Rus, D., Slotine, J.J.: Decentralized, adaptive coverage control for networked robots. Int. J. Robot. Res. 28(3), 357–375 (2009)
3. Cortes, J., Martinez, S., Karatas, T., Bullo, F.: Coverage control for mobile sensing networks. IEEE Trans. Robot. Autom. 20(2), 243–255 (2004)
4. Doyle, J., Glover, K., Khargonekar, P., Francis, B.: State-space solutions to standard h 2 and h ∞ control problems. IEEE Trans. Autom. Control 34(1), 831–874 (1989)
5. Chen, B.S., Lee, T., Feng, J.: A nonlinear h ∞ control design in robotic systems under parameter perturbation and external disturbance. Int. J. Control 59(2), 439–461 (1994)
6. Demir, O., Keskin, I., Cetin, S.: Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach. Nonlinear Dyn. (2012). doi:10.1007/s11071-011-0135-y
7. Hu, Q.: Sliding mode maneuvering control and active vibration damping of three-axis stabilized flexible spacecraft with actuator dynamics. Nonlinear Dyn. 52, 227–248 (2008). doi:
8. Wang, C.-C., Yau, H.-T.: Nonlinear dynamic analysis and sliding mode control for a gyroscope system. Nonlinear Dyn. 66, 53–65 (2011). doi:
9. Mousavi, S., Ranjbar-Sahraei, B., Noroozi, N.: Output feedback controller for hysteretic time-delayed mimo nonlinear systems. Nonlinear Dyn. (2011). doi:10.1007/s11071-011-0204-2
10. Lin, D., Wang, X., Yao, Y.: Fuzzy neural adaptive tracking control of unknown chaotic systems with input saturation. Nonlinear Dyn. (2011). doi:10.1007/s11071-011-0196-y
11. Chen, B.-S., Lee, C.-H., Chang, Y.-C.: H ∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans. Fuzzy Syst. 4(1), 32–43 (1996)
12. Ranjbarsahraei, B., Roopaei, M., Khosravi, S.: Adaptive fuzzy formation control for a swarm of nonholonomic differentially driven vehicles. Nonlinear Dyn. 67(4), 2747–2757 (2011). doi:
13. Pimenta, L.C.A., Schwager, M., Lindsey, Q., Kumar, V., Rus, D., Mesquita, R.C., Pereira, G.A.S.: Simultaneous coverage and tracking (scat) of moving targets with robot networks. In: Proceedings of the Eighth International Workshop on the Algorithmic Foundations of Robotics (WAFR 08) (2008)
14. Ranjbar-Sahraei, B., Shabaninia, F., Nemati, A., Stan, S.-D.: A novel robust decentralized adaptive fuzzy control for swarm formation of multi-agent systems. IEEE Trans. Ind. Electron. 99, 1 (2012)
15. Butler, Z., Rus, D.: Controlling mobile sensors for monitoring events with coverage constraints. In: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04, New Orleans, LA, vol. 2, pp. 1568–1573 (2004)
16. Bullo, F., Cortes, J., Martinez, S.: In: Distributed Control of Robotic Networks. Applied Mathematics Series (2009). Available at http://www.coordinationbook.info
17. Breitenmoser, A., Schwager, M., Metzger, J.C., Siegwart, R., Rus, D.: Voronoi coverage of non-convex environments with a group of networked robots. In: Proc. of the International Conference on Robotics and Automation (ICRA 10), Anchorage, AK, pp. 4982–4989 (2010)
18. Delle Fave, F., Canu, S., Iocchi, L., Nardi, D., Ziparo, V.: Multi-objective multi-robot surveillance. In: Autonomous Robots and Agents. 4th International Conference on ICARA 2009, Wellington, New Zealand, pp. 68–73 (2009)
19. Kolling, A., Carpin, S.: Multi-robot surveillance: an improved algorithm for the graph-clear problem. In: Robotics and Automation. IEEE International Conference on ICRA 2008, Pasadena, CA, pp. 2360–2365 (2008)
20. Schwager, M., Rus, D., Slotine, J.J.: Unifying geometric, probabilistic, and potential field approaches to multi-robot deployment. Int. J. Robot. Res. 30(3), 371–383 (2011)
21. Schwager, M., McLurkin, J., Slotine, J.J.E., Rus, D.: From theory to practice: distributed coverage control experiments with groups of robots. In: Experimental Robotics: The Eleventh International Symposium, vol. 54, pp. 127–136. Springer, Berlin (2008)
22. Schwager, M., Michael, N., Kumar, V., Rus, D.: Time scales and stability in networked multi-robot systems. In: Proc. of the International Conference on Robotics and Automation (ICRA 11), Shanghai, China (2011)
23. Schwager, M., Slotine, J.J.E., Rus, D.: Decentralized, adaptive control for coverage with networked robots. In: Proceedings of the International Conference on Robotics and Automation (ICRA 07), Roma, Italy, pp. 3289–3294 (2007)
24. Sahraei, B.R., Shabaninia, F.: A robust H ∞ control design for swarm formation control of multi-agent systems: A decentralized adaptive fuzzy approach. In: 3rd International Symposium on Resilient Control Systems (ISRCS10), Idaho Falls, ID, pp. 79–84 (2010)
25. Wang, L.: A Course in Fuzzy Systems and Control. Prentice-Hall, Englewood Cliffs (1997) - 作者单位：1. Young Researchers Club, Sepidan Branch, Islamic Azad University, Sepidan, Iran2. Department of Electronics, Sepidan Branch, Islamic Azad University, Sepidan, Iran
- 刊物类别：Engineering
- 刊物主题：Vibration, Dynamical Systems and Control
Mechanics
Mechanical Engineering
Automotive and Aerospace Engineering and Traffic - 出版者：Springer Netherlands
- ISSN：1573-269X
文摘
In this paper, a decentralized adaptive control scheme for multi-robot coverage is proposed. This control method is designed based on centroidal Voronoi configuration integrated with robust adaptive fuzzy control techniques. We consider simple single integrator mobile robots used for covering dynamical environments, where an adaptive fuzzy logic system is used to approximate the unknown parts of control law. A robust coverage criterion is used to attenuate the adaptive fuzzy approximation error and measurement noises to a prescribed level. Therefore, the robots motion is forced to obey solutions of a coverage optimization problem. The advantages of the proposed controller can be listed as robustness to external disturbances, computation uncertainties, and measurement noises, while applicability on dynamical environments. A Lyapunov-function based proof is given of robust stability, i.e. convergence to the optimal positions with bounded error. Finally, simulation results are demonstrated for a swarm coverage problem simultaneous with tracking mobile intruders.