Plasmonic sensors based on nanostructured metal substrates offer a promising solution for on-site implementation and continuous monitoring of process liquids due to their compact design, cost-effectiveness, and rapid sensor response. The sensors are qualified for the functionalization with biological recognition elements and thus for biosensing. A functionalization with stimulus-responsive hydrogels further enhances their utility by enabling selective determination of specific substances in complex solutions. However, challenges arise in accurately interpreting the sensor signals due to the nonlinearity between the swelling curve of the hydrogel and the sensor signal and due to interferences from nontarget substances. An important objective of this study is to develop a methodology to accurately determine the concentration of a target substance in a multicomponent solution, eliminating the influence of interfering substances. For this, it is imperative to enhance the comprehension of the system, elucidating the impact of the hydrogel’s swelling state and the composition on the sensor signal. An analytical model is presented, conveying a linear relationship between the sensor signal and the volume fraction of each constituent in the hydrogel. Based on the proposed model, a novel difference method is established to eliminate the influence of interfering substances, particularly at low concentrations of interfering substances. In a proof-of-concept, using an ethanol-sensitive hydrogel for detection of ethanol in aqueous ethanol–glucose solution, the method was validated, showing a negligible impact of glucose concentration on the result.