Reference
S. Lin, B. De Schutter, Y. Xi, and H. Hellendoorn, "Fast model predictive
control for urban road networks via MILP,"
IEEE Transactions
on Intelligent Transportation Systems, vol. 12, no. 3, pp. 846-856,
Sept. 2011.
Abstract
In this paper, an advanced control strategy, i.e. Model Predictive Control
(MPC), is applied to control and coordinate urban traffic networks. However,
due to the nonlinearity of the prediction model, the optimization of MPC is a
nonlinear non-convex optimization problem. In this case, the on-line
computational complexity becomes a big challenge for the MPC controller, if it
is implemented in real-life traffic network. To overcome this problem, the
on-line optimization problem is reformulated into a Mixed-Integer Linear
Programming (MILP) optimization problem, so as to increase the real-time
feasibility of the MPC control strategy. The new optimization problem can be
solved very efficiently by existing MILP solvers, and the global optimum of the
problem is guaranteed. Moreover, we propose an approach to reduce the
complexity of the MILP optimization problem even further. The simulation
results show that the MILP-based MPC controllers can reach the same
performance, but the time taken to solve the optimization becomes only a few
seconds, which is a significant reduction compared with the time required by
the original MPC controller.
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BibTeX
@article{LinDeS:11-001,
author = {Lin, Shu and De Schutter, Bart and Xi, Yugeng and Hellendoorn,
Hans},
title = {Fast Model Predictive Control for Urban Road Networks via
{MILP}},
journal = {IEEE Transactions on Intelligent Transportation Systems},
volume = {12},
number = {3},
pages = {846--856},
month = sep,
year = {2011}
}