Considerable amounts of water can be saved by automating irrigation canals. The design of most of the practical automatic controllers rely on a simplified model of the irrigation canal. This model can be obtained from measured data (identification) or can be formulated (white box models) assuming simplifications in the physical concepts and using the canal geometry. Several models of this kind are presently available. Moreover, short canals reveal a resonance problem, due to the back and forth of waves. This paper is focused on how to choose a suitable model for short canal pools with the purpose of control design. Four simple models are applied to two different types (resonant and non-resonant) of short canals: First order transfer function based on the Hayami model, Muskingum model, Integrator Delay (ID), and Integrator Delay plus Zero (IDZ). Model predictive controllers are developed based on these models and they are tested numerically and experimentally in order to evaluate their contribution to the control effectiveness. The controllers based on the ID and IDZ model showed the best performance.
a b s t r a c tIrrigation or drainage canals can be controlled by model predictive control (MPC). Applying MPC with an internal model in the presence of unknown disturbances in some cases can lead to steady state offset. Therefore an additional component should be implemented along with the MPC. A new method eliminating the offset has been developed in this paper for MPC. It is based on combining two basic approaches of MPC. It has been implemented to control water levels in the three-pool UPC laboratory canal and further numerically tested using a test case benchmark proposed by the American Society of Civil Engineers (ASCE). It has been found that the developed offset-free method is able to eliminate the steady-state offset, while taking into account known and unknown disturbances.
Centralized model predictive controllers are common in water systems. The control action variable can be the discharge, and the subsystems (canal pools) are modeled separately. This paper focuses on short canal pools where the interactions are stronger between canal pools. Could this procedure be better if gate openings were used as control action variables and the interconnected system were modeled for the controller? Model predictive controllers (MPCs) were developed using the discharge and the gate opening as control action variable and tested experimentally using the laboratory canal of the Technical University of Catalonia. It was found that for centralized MPCs for short canal pools, the use of gate opening as control action variable is more beneficial than discharge. Another additional advantage is that in this way it is possible to put constraints on the gate opening and the change of gate opening, which are important to the limitations of the physical system.
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