PROSPECTS FOR OPTIMAL CONTROL OF HYDRAULIC PROCESSES IN WATER MANAGEMENT FACILITIES AND THE APPLICATION OF ARTIFICIAL INTELLIGENCE
Abstract
Effective control of hydraulic processes in water management facilities, including irrigation canals, pumping stations, and reservoirs, is increasingly important under water scarcity and climate change. Traditional control methods, such as PID regulators and manual operation, often fail to address nonlinear hydraulic behavior and rapidly changing conditions. This study reviews current approaches to optimal hydraulic control and evaluates the potential of artificial intelligence methods, including neural networks and reinforcement learning. Analysis of recent research indicates that AI-based control systems can reduce water consumption by 15–40% and energy use by 20–30%, supporting the development of efficient smart water management systems.