Abstract:
We consider the problem of estimating flow state in real time in large-scale open channel networks. After constructing a state space model of the flow based on the Saint-Venant equations, we implement the optimal sequential importance resampling (SIR) filter to perform state estimation using some additional flow measurements. The estimation method is implemented using a model of a network of 19 subchannels and one reservoir, Clifton Court Forebay, in Sacramento-San Joaquin Delta in California and the numerical results are presented.
Publication date:
June 1, 2012
Publication type:
Conference Paper
Citation:
Rafiee, M., Barrau, A., & Bayen, A. (2012). State Estimation in Large-Scale Open Channel Networks Using Particle Filters. 2012 American Control Conference (ACC), 1104–1110. https://doi.org/10.1109/ACC.2012.6315186