Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31830
Hybrid Control of Networked Multi-Vehicle System Considering Limitation of Communication Range

Authors: Toru Murayama, Akinori Nagano, Zhi-Wei Luo


In this research, we study a control method of a multivehicle system while considering the limitation of communication range for each vehicles. When we control networked vehicles with limitation of communication range, it is important to control the communication network structure of a multi-vehicle system in order to keep the network-s connectivity. From this, we especially aim to control the network structure to the target structure. We formulate the networked multi-vehicle system with some disturbance and the communication constraints as a hybrid dynamical system, and then we study the optimal control problems of the system. It is shown that the system converge to the objective network structure in finite time when the system is controlled by the receding horizon method. Additionally, the optimal control probrems are convertible into the mixed integer problems and these problems are solvable by some branch and bound algorithm.

Keywords: Hybrid system, multi-vehicle system, receding horizon control, topology control.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1260


[1] C. A. Rabbath, C. -Y. Su and A. Tsourdos, "Special issue on multivehicle systems cooperative control with application," IEEE Transaction on Control Systems Technology, Vol. 15, No. 4, 2007.
[2] R. M. Murray, "Recent research in cooperative control of multivehicle systems," Journal of Dynamic Systems, Measurement, and Control, Vol. 129, No. 5, pp. 569-754, 2007.
[3] J. A. Fax and R. M. Murray, "Infomation frow and cooperative control of vehicle formations," IEEE Transaction on Automatic Control, Vol. 49, No. 9, pp. 1465-1476, 2004.
[4] W. B. Dunbar and R. M. Murray, "Distributed receding horizon control for multi-vehicle formation stabilization," Automatica , Vol. 42, No. 4, pp. 549-558, 2006.
[5] P. Santi, "Topology Control in Wireless Ad Hoc and Sensor Networks ," Wiley, 2005.
[6] M. M. Zavlanos and G. J Pappas, "Potential fields for maintaining connectivity of mobile network," IEEE Transaction on robotics, Vol. 23, No. 4, pp. 812-816, 2007.
[7] M. M. Zavlanos and G. J Pappas, "Distributed connectivity control of mobile networks," IEEE Transaction on robotics, Vol. 24, No. 6, pp. 1416-1428, 2008.
[8] D. Mayne, J. Rawlings, C. Rao and P. Scokaert, "Constrained model predictive control: stability and optimality," Automatica, Vol. 36, pp.789- 814, 2000.
[9] A. Bemporad M. Morari, V. Dua and E. N. Pistikopoulos "The explicit linear quadratic regulator for constrained systems," Automatica , Vol. 38, No. 1, pp. 3-20, 2002.
[10] A. Bemporad and M. Morari, "Control of systems integrating logic, dynamics and constraints," Automatica, Vol. 35, pp. 407-427, 1999.
[11] B. Korte and J. Vygen, "Combinatorial optimization: theory and algorithms," Springer, 2005.
[12] C. Godsil and G. Royle, "Algebraic Graph Theory," Springer-Verlag, 2001.
[13] S. Boyd and L. Vandeberghe, "Convex opmization," Cambridge Univ. Press, 2004
[14] A. Ben-Tal, L. E. Ghaoui and A. Nemirovski, "Robust Optimization," Princeton Univ. Press, 2009.
[15] F. Tedesco, D. M. Raimondo, A. Casavola and J. Lygeros, "Distributed collision avoidance for interacting vehicles: a command governor approach," 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys-10), 2010.