
Title:  De SaintVenant equationsbased model assessment in model predictive control of open channel flow   Authors:  M. Xu, R.R. Negenborn, P.J. van Overloop, N.C. van de Giesen 
 Journal:  Advances in Water Resources   
 Abstract:  Model predictive control (MPC) is a modelbased control technique that uses an optimization algorithm to generate optimal control actions. Based on the model used in optimization, MPC approaches can be categorized as linear or nonlinear. Both classes have advantages and disadvantages in terms of control accuracy and computational time. A typical linear model in open channel water management is the Integrator Delay (ID) model, while a nonlinear model usually refers to the SaintVenant equations. In earlier work, we proposed the use of linearized SaintVenant equations for MPC, where the model is formulated in a linear timevarying format and timevarying parameters are estimated outside of the optimization. Quadratic Programming (QP) is used to solve the optimization problem. However, the control accuracy of such an MPC scheme is not clear. In this paper, we compare this approach with an MPC scheme that uses Sequential Quadratic Programming (SQP) to solve the optimization problem. Because the estimation of the timevarying parameters is integrated in the optimization in SQP, the solutions from SQPbased MPC are expected to be superior to the solutions of QPbased approach. However, SQP can be computationally expensive. A simulation experiment illustrates that the QPbased MPC approach using a linearized SaintVenant model has an accurate approximation of the control performance of SQP. 
 Reference:  De SaintVenant equationsbased model assessment in model predictive control of open channel flow. M. Xu, R.R. Negenborn, P.J. van Overloop, N.C. van de Giesen. Advances in Water Resources, vol. 49, no. 2012, pp. 3745, 2012. 
 BibTeX:  @article{MinNegenborn:12,
author = {M. Xu and R. R. Negenborn and P. J. {van Overloop} and N. C. {van de Giesen}},
title = {De SaintVenant equationsbased model assessment in model predictive control of open channel flow},
journal = {Advances in Water Resources},
year = {2012},
pages = {3745},
volume = {49},
number = {2012}
}   Request:  A
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