Control system for sluice gates flow in irrigation canals

Abstract EN

Water has become the most important problem in relations between the countries of the Middle East in the recent years.

It occupies an important place on the agenda of several international organizations.

Water control and reduction loss of water discharge is a major challenge facing the design of new irrigation projects.

A downstream control algorithm for demand operation of irrigation system is proposed in this paper through maintaining downstream end discharge of the canal at the target point by manipulating the upstream sluice gate in real time.

The control of the water level and discharge for canal irrigation system has non-linear, time-varying and uncertainty characteristics.

This paper compares three control algorithms; conventional PID, fuzzy neural network PID, and PID neural network control based on fuzzy neural network model.

The simulation results show that the first control has larger over-shoot, longer adjusting time and poorer anti-interference ability.

The second control overcomes above-mentioned short-comings, small overshoot, faster response speed, very small steady state error.

Third control produces better effects than previous controllers in both steady performance and dynamic performance, including shorter steady-state time, nonovershot, no oscillator, and higher dynamic tracking rate.