Abstract
A comparative study about two models, Muskingum and integrator-delay (ID) models, for canal control is presented. The former is a simplified hydrological model which is very simple and extensively used in hydraulic engineering for simulation and prediction. The latter is also a model with physical meaning and is widely used for irrigation canals control. Due to a lack of general awareness of Muskingum prediction model in regulation from the control community, authors present this comparative study with the ID control model. Both models have been studied and analyzed for control purposes. This study has been carried out and validated in a real irrigation canal, at Aghili irrigation district in Iran, using two traditional control approaches, PID with feedback and predictive control. The results demonstrate the advantages and drawbacks of both models, showing the benefits and limitations of using the widespread Muskingum model among the hydraulics scientific community for control design.
Highlights
Management of open-flow canal systems requires accurate control models of flow transfer
The results demonstrate the advantages and drawbacks of both models, showing the benefits and limitations of using the widespread Muskingum model among the hydraulics scientific community for control design
For the PI with a Smith predictor (SP) scheme designed by pole placement technique [59,60,61], it can be observed that the results considering the real plant and the continuous ID model using the PI designed with discrete ID model (ZOH, Ts = 60 s) are very similar
Summary
Management of open-flow canal systems requires accurate control models of flow transfer. Open-flow canals are large parameter-distributed systems that can be described with Saint-Venant equations [1, 2]. These nonlinear partial differential equations (PDE) represent water dynamics in a precise and complete manner and, for an arbitrary geometry, there is no analytical solution. The stability of their solution cannot be guaranteed and depends on the discretization time Taking into account this fact, usually Muskingum model has been used by hydraulic engineers as a prediction model in rivers and in irrigation canals [10, 11] but so far not as a control model. In control design or in the computation of control actions, the complexity of the characteristic model is directly proportional to the complexity of the control techniques and their implementation. A classical way to control irrigation canals is to design controllers based on linear models
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