Mathematical Modelling and Advanced Control Techniques for Irrigation Canal Management

Abstract

Efficient water management in irrigation canal systems is vital for sustainable agriculture and environmental conservation. This thesis presents advanced control strategies to optimize water distribution and address the uncertainties inherent in such systems. A comprehensive mathematical modelling framework is developed, incorporating key hydraulic variables such as water levels and gate openings to capture canal dynamics. This model is validated through simulations on real-world systems, including the Corning Canal, Maricopa Stanfield Canal, and Distributary-36 of the Tungabhadra Left Bank Canal (TLBC), and shows strong predictive performance across varying flow conditions. The study focuses on the influence of hydraulic parameter uncertainties, particularly the roughness coefficient. Simulation results highlight the significant impact of such uncertainties, reinforcing the need to incorporating these uncertainties into the control-oriented model for designing an efficient controller to enhance control effectiveness. The thesis introduces gain scheduled Proportional-Integral (GS-PI) controllers for single-pool canal models. Frequency domain as well as time-domain analysis show that GS-PI controllers outperform traditional PI controllers by providing faster settling times, reduced and consistent overshoot, and robust performance across discharge conditions. Quantitative Feedback Theory (QFT) is also explored for controller design under parameter uncertainties. While its initial response is slower, the QFT controller ensures long-term stability and robustness. The study further extends to multi-pool systems by developing a decoupled model that simplifies multivariable controller design. Simulations confirm the GS controller's effectiveness in maintaining desired water levels and rejecting disturbances under varying operating scenarios. Overall, this thesis offers practical modelling and control solutions that improve irrigation canal operations' reliability, adaptability, and efficiency, contributing to more resilient water management systems.