Electrical and Electronic Engineering - Theses

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End date: 2021 × Type: PhD thesis × Subject: control systems × Subject: model predictive control ×

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    Modelling and control design of river systems
    Foo, Mathias Fui Lin ( 2011)
    Farming consumes a large amount of water usage and it is reported that large portion of this water is wasted through inefficient water distribution from river to farms. More efficient water distribution and preservation of environmental demands can be achieved through better control and decision support systems. In order to design better control and decision support systems, a river model is required. This model needs to be able to capture the relevant river dynamics and easy to be used for control design. Traditionally, the Saint Venant equations have been used to model river systems. These equations are nonlinear hyperbolic partial differential equation (PDE) and are solved numerically using Preissmann scheme. The simulated Saint Venant equations are compared against operational data from the Broken River, and it is found that the Saint Venant equations are accurate in representing the river systems. Through further study, it is found that a single segmentation, i.e. treating the river as one long stretch with uniform geometry is sufficiently accurate for representation of the river for the purpose of control design. For the representation of meandering river, the Saint Venant equations are as accurate a two-dimensional flow model. The nonlinearities in the Saint Venant equations are also investigated. From the nonlinearity test, it is found that the Saint Venant equations are approximately linear within an operating region. The Saint Venant equations are difficult to use for control design. An alternative model is therefore sought. Based on the operational data from the Broken River, simple time delay model (TDM) and integrator delay model (IDM) are proposed and estimated using system identification procedures. These models are found to be accurate in capturing the relevant dynamics of the river system. Furthermore, they are easy to use for control design. It is found that the time delay varies with the flow and hence controllers must be robust to variations in the time delay. A comparison between both TDM and IDM and the Saint Venant equations shows that they are as accurate as the Saint Venant equations within the operating range. The TDM and IDM are desirable as they are easier to be used for control design and decision support system. The TDM and IDM are used to design Model Predictive Control (MPC) to control the river system. The choice of using MPC is motivated by the fact that MPC handles constraints very well. Despite that, tuning the weights in the MPC cost function is not trivial. The methods of reverse engineering are used to obtain these weights. Building on the results of existing method of reverse engineering used in the literatures, two additional methods are developed. In addition, the design of MPC from scratch is also considered. A realistic year long simulations using both MPCs on the Broken River is carried out. The MPCs are compared with the current manual operation and a decentralised control configuration. The results show that with MPCs, significant water savings, improvement of water delivery service to the irrigators and the environmental demands satisfaction are achieved.