Abstract: As the core unit ensuring thickness precision in strip rolling, the hydraulic Automatic Gauge Control (AGC) system directly determines the quality of high-performance metal materials. This paper systematically reviews the technological evolution of hydraulic AGC, dividing it into three logical stages: servo execution based on analog regulation, calculation-based precision control grounded in theoretical models, and adaptive compensation leveraging intelligent algorithms. The analysis focuses on evolutionary characteristics in response speed, model accuracy, and nonlinear compensation at each stage. Addressing the current control bottleneck caused by strong coupling between hydraulic drive dynamics and mechanical systems, this paper proposes a novel predictive management and control architecture that deeply integrates physical mechanisms with real-time data. Four key technical pathways are elaborated: high-fidelity mechanistic modeling, variable-fidelity surrogate model reduction, cloud-edge-end collaborative regulation, and digital twin-enabled full lifecycle perception. This framework aims to enhance system robustness under complex operating conditions, providing theoretical support for the transformation of hydraulic AGC systems towards digital and intelligent and autonomous operation.