Hybrid Control of Networked Multi-Vehicle System Considering Limitation of Communication Range
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:57791", author = "Toru Murayama and Akinori Nagano and Zhi-Wei Luo", title = "Hybrid Control of Networked Multi-Vehicle System Considering Limitation of Communication Range", abstract = "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.", volume = "5", number = "11", pages = "1345-7", }