Reference:
Z. Hidayat,
Zs. Lendek,
R. Babuska, and
B. De Schutter,
"Fuzzy observer for state estimation of the METANET traffic model,"
Proceedings of the 13th International IEEE Conference on
Intelligent Transportation Systems (ITSC 2010), Madeira Island,
Portugal, pp. 19-24, Sept. 2010.
Abstract:
Traffic control has proven an effective measure to reduce traffic
congestion on freeways. In order to determine appropriate control
actions, it is necessary to have information on the current state of
the traffic. However, not all traffic states can be measured (such as
the traffic density) and so state estimation must be applied in order
to obtain state information from the available measurements. Linear
state estimation methods are not directly applicable, as traffic
models are in general nonlinear. In this paper we propose a nonlinear
approach to state estimation that is based on a Takagi-Sugeno (TS)
fuzzy model representation of the METANET traffic model. By
representing the METANET traffic model as a TS fuzzy system, a
structured observer design procedure can be applied, whereby the
convergence of the observer is guaranteed. Simulation results are
presented to illustrate the quality of the estimate.