Level control systems often exhibit nonlinear characteristics, making the robust model identification and, consequently, the dynamic controller’s tuning a challenging task. The use of adaptive control systems is highly beneficial in these contexts, as they enable automatic adjustment to variations and nonlinearities inherent in the level control process. In particular, this work investigates the application of two adaptive control approaches by Gain Scheduling (GS): the interpolation implementation and the range implementation. Both implementations were applied in a real-level control didactic plant, using Proporcional Integral (PI) type controllers. The study aimed to compare GS approaches with the controller design based on the Internal Model Control (IMC) method. The results showed the superior performance of GS implementations about IMC. In the first test scenario, the GS approach achieved an average reduction of 64.49% in Integral Absolute of the Error (IAE) and 60.67% in Integral of the Time-weighted Absolute Error (ITAE), while in the second scenario, the reduction reached 54.43% in IAE and 46.59% ITAE. These results highlight the impressive ability of GS-based implementations to understand the nonlinearities inherent in the level control system, positioning them as a promising path to designing controllers less susceptible to system nonlinearities.