A non-iterative cascaded predictive control approach for control of irrigation canals

Irrigation canals transport water from water sources (such as large rivers and lakes) to water users (such as farmers). Irrigation canals are typically very large in nature, covering vast geographical areas, and involving a significant number of control actuators, such as pumps, gates, and locks. The control of such canals is aimed at guaranteeing the adequate delivery of water with minimal water spillage and with minimal control structure usage. To take into account forecasts on, e.g., water consumption and weather, model predictive control (MPC) can be used to determine which actions to take. For large-scale systems, in which different parts of the canal are owned by different parties, distributed MPC control could then be employed. Although iterative distributed MPC approaches proposed earlier in the literature may yield overall optimal performance, the amount of iterations required before achieving this performance may be large, and thus require a significant amount of time. In this paper, the structure of systems consisting of serially interconnected subsystems is exploited to obtain an efficient non-iterative, cascaded MPC scheme. Simulation studies on a 7-reach irrigation canal illustrate the performance of this non-iterative scheme in comparison with an iterative scheme.