Enhancing Robust Control of Irrigation Canal Systems with Quantitative Feedback Theory (QFT)

Water, as a renewable resource, is critical for agricultural sustainability, yet managing its distribution through irrigation canals is complicated by uncertainties in hydraulic parameters, particularly the Manning roughness coefficient. While canal automation techniques improve system performance, traditional control strategies struggle with unknown variations, leading to inefficiencies. This paper presents Quantitative Feedback Theory (QFT) as a robust control strategy to address both structured and unstructured uncertainties in irrigation systems. Focusing on the Distributary-36, of the Tungabhadra Left Bank Canal (TLBC) system, we analyze the impact of ±30% uncertainty in roughness coefficients and design a QFT-based controller to maintain stability across these variations. Simulations show that the QFT controller ensures effective flow control and system stability, offering a more reliable solution for water management under fluctuating conditions.