Modeling and Control Design of a Centralized Adaptive Cruise Control System
A vehicle driving with an Adaptive Cruise Control
System (ACC) is usually controlled decentrally, based on the
information of radar systems and in some publications based on
C2X-Communication (CACC) to guarantee stable platoons. In this
paper we present a Model Predictive Control (MPC) design of a
centralized, server-based ACC-System, whereby the vehicular platoon
is modeled and controlled as a whole. It is then proven that the
proposed MPC design guarantees asymptotic stability and hence
string stability of the platoon. The Networked MPC design is
chosen to be able to integrate system constraints optimally as well
as to reduce the effects of communication delay and packet loss.
The performance of the proposed controller is then simulated and
analyzed in an LTE communication scenario using the LTE/EPC
Network Simulator LENA, which is based on the ns-3 network
simulator.
[1] R. Rasshofer, "Functional requirements of future automotive radar
systems,” Proc. Eur. Radar Conf., pp. 1538–1541, 2007.
[2] D. Swaroop, "String stability of interconnected systems: An application
to platooning in automated highway systems,” Ph.D. dissertation, Univ.
Calif., Berkeley, 2007.
[3] D. Swaroop, J. Hedrick, C. Chien, and P. Ioannou, "A comparison of
spacing and headway control laws for automatically controlled vehicles,”
Vehicle Syst. Dynamics Journal, vol. 23, no. 8, pp. 597–625, 1994.
[4] R. Rajamani and C. Zhu, "Semi-autonomous adaptive cruise control
systems,” IEEE Transactions on Vehicular Technology, vol. 51, no. 5,
pp. 1186–1192, 2002.
[5] G. N. et al., "String-stable cacc design and experimental validation:
A frequency-domain approach,” IEEE Transactions on Vehicular
Technology, vol. 59, no. 9, pp. 4268–4279, 2010.
[6] X. Liu and S. Mahal, "Effects of communication delay on string stability
in vehicle platoons,” IEEE Intelligent Transportation Systems Conf.
Preceedings, pp. 625–630, 2001.
[7] S. O¨ ncu¨ et al., "String stability of interconnected vehicles under
communication constraints,” IEEE Conf. on Decision and Control, pp.
2459–2464, 2012.
[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] G. N. et al., "Explicit mpc design and performance evaluation of an acc
stop-&-go,” American Control Conference, 2002.
[10] L.-H. Luo, H. Liu, P. Li, and H. Wang, "Model predictive control for
adaptive cruise control with multi-objectives: Comfort, fuel-economy,
safety and car-following,” J Zhejiang Univ-Sci A (Appl Phys & Eng),
vol. 11, no. 3, pp. 191–201, 2010.
[11] V. Bageshwar, W. Garrard, and R. Rajamani, "Model predictive control
of transitional maneuvers for adaptive cruise control vehicles,” IEEE
Transactions on Vehicular Technology, vol. 53, no. 5, pp. 1573–1585,
2004.
[12] J. Kautsky, N. Nichols, and P. V. Dooren, "Robust pole assignment in
linear state feedback,” International Journal of Control, vol. 41, pp.
1129–1155, 1985.
[13] MATLAB, version 7.9.1 (R2009b). Natick, Massachusetts: The
MathWorks Inc., 2010.
[14] C. Rao and J. Rawlings, "Linear programming and model predictive
control,” Journal of Process Control, vol. 10, pp. 283–289, 2000.
[15] A. Bemporad, F. Borrelli, and M. Morari, "The explicit solution of
constrained lp-based receding horizon control,” Proc. 39th IEEE Conf.
on Decision and Control, vol. 1, pp. 632–637, 2000.
[16] E. Gilbert and K. Tan, "Linear systems with state and control constraints:
The theory and application of maximal output admissible sets,” IEEE
Transactions on Automatic Control, vol. 36, no. 9, pp. 1008–1020, 1991.
[17] Z. Li, L. Wang, X. Lai, and S. Xu, "Stability of constrained model
predictive control for networked control systems with data packet
dropout,” IEEE Int. Conf. on Automation and Logistics, pp. 3018–3023,
2007.
[18] Lte-epc network simulator (lena). (Online). Available:
http://networks.cttc.es/mobile-networks/software-tools/lena/
[19] Ns3. (Online). Available: http://www.nsnam.org/
[1] R. Rasshofer, "Functional requirements of future automotive radar
systems,” Proc. Eur. Radar Conf., pp. 1538–1541, 2007.
[2] D. Swaroop, "String stability of interconnected systems: An application
to platooning in automated highway systems,” Ph.D. dissertation, Univ.
Calif., Berkeley, 2007.
[3] D. Swaroop, J. Hedrick, C. Chien, and P. Ioannou, "A comparison of
spacing and headway control laws for automatically controlled vehicles,”
Vehicle Syst. Dynamics Journal, vol. 23, no. 8, pp. 597–625, 1994.
[4] R. Rajamani and C. Zhu, "Semi-autonomous adaptive cruise control
systems,” IEEE Transactions on Vehicular Technology, vol. 51, no. 5,
pp. 1186–1192, 2002.
[5] G. N. et al., "String-stable cacc design and experimental validation:
A frequency-domain approach,” IEEE Transactions on Vehicular
Technology, vol. 59, no. 9, pp. 4268–4279, 2010.
[6] X. Liu and S. Mahal, "Effects of communication delay on string stability
in vehicle platoons,” IEEE Intelligent Transportation Systems Conf.
Preceedings, pp. 625–630, 2001.
[7] S. O¨ ncu¨ et al., "String stability of interconnected vehicles under
communication constraints,” IEEE Conf. on Decision and Control, pp.
2459–2464, 2012.
[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] G. N. et al., "Explicit mpc design and performance evaluation of an acc
stop-&-go,” American Control Conference, 2002.
[10] L.-H. Luo, H. Liu, P. Li, and H. Wang, "Model predictive control for
adaptive cruise control with multi-objectives: Comfort, fuel-economy,
safety and car-following,” J Zhejiang Univ-Sci A (Appl Phys & Eng),
vol. 11, no. 3, pp. 191–201, 2010.
[11] V. Bageshwar, W. Garrard, and R. Rajamani, "Model predictive control
of transitional maneuvers for adaptive cruise control vehicles,” IEEE
Transactions on Vehicular Technology, vol. 53, no. 5, pp. 1573–1585,
2004.
[12] J. Kautsky, N. Nichols, and P. V. Dooren, "Robust pole assignment in
linear state feedback,” International Journal of Control, vol. 41, pp.
1129–1155, 1985.
[13] MATLAB, version 7.9.1 (R2009b). Natick, Massachusetts: The
MathWorks Inc., 2010.
[14] C. Rao and J. Rawlings, "Linear programming and model predictive
control,” Journal of Process Control, vol. 10, pp. 283–289, 2000.
[15] A. Bemporad, F. Borrelli, and M. Morari, "The explicit solution of
constrained lp-based receding horizon control,” Proc. 39th IEEE Conf.
on Decision and Control, vol. 1, pp. 632–637, 2000.
[16] E. Gilbert and K. Tan, "Linear systems with state and control constraints:
The theory and application of maximal output admissible sets,” IEEE
Transactions on Automatic Control, vol. 36, no. 9, pp. 1008–1020, 1991.
[17] Z. Li, L. Wang, X. Lai, and S. Xu, "Stability of constrained model
predictive control for networked control systems with data packet
dropout,” IEEE Int. Conf. on Automation and Logistics, pp. 3018–3023,
2007.
[18] Lte-epc network simulator (lena). (Online). Available:
http://networks.cttc.es/mobile-networks/software-tools/lena/
[19] Ns3. (Online). Available: http://www.nsnam.org/
@article{"International Journal of Information, Control and Computer Sciences:67701", author = "Markus Mazzola and Gunther Schaaf", title = "Modeling and Control Design of a Centralized Adaptive Cruise Control System", abstract = "A vehicle driving with an Adaptive Cruise Control
System (ACC) is usually controlled decentrally, based on the
information of radar systems and in some publications based on
C2X-Communication (CACC) to guarantee stable platoons. In this
paper we present a Model Predictive Control (MPC) design of a
centralized, server-based ACC-System, whereby the vehicular platoon
is modeled and controlled as a whole. It is then proven that the
proposed MPC design guarantees asymptotic stability and hence
string stability of the platoon. The Networked MPC design is
chosen to be able to integrate system constraints optimally as well
as to reduce the effects of communication delay and packet loss.
The performance of the proposed controller is then simulated and
analyzed in an LTE communication scenario using the LTE/EPC
Network Simulator LENA, which is based on the ns-3 network
simulator.
", keywords = "Adaptive Cruise Control, Centralized Server, Networked Model Predictive Control, String Stability.", volume = "8", number = "7", pages = "1197-5", }
