Modeling of Coupled-Tank System Using Fuzzy Takagi-Sugeno Model. This paper describes modeling of coupledtanksystem based on data measurement using fuzzy Takagi-Sugeno model. The fuzzy clustering method of Gustafson-Kessel algorithm is used to classify input-output data into several clusters based on distance similarity of a member ofinput-output data from center of cluster. The formed clusters are projected orthonormally into each linguistic variablesof premise part to determine membership function of fuzzy Takagi-Sugeno model. By estimating data in each cluster,the consequent parameters of fuzzy Takagi-Sugeno model are calculated using weighted least-squares method. Theresulted fuzzy Takagi-Sugeno model is validated by using model performance parameters variance-accounted-for (VAF)and root mean square (RMS) as performance indicators. The simulation results show that the fuzzy Takagi-Sugenomodel is able to mimic nonlinear characteristic of coupled-tank system with good value of model performanceindicators.