Background Acquiring a good model is important for representing a real system especially in complex chemical processes. In this work, type-2 fuzzy logic with the Karmen-Mendel algorithm is proposed to model sequential ionic liquid dissolution-solid acid saccharification. The fuzzy calculation framework was regressed using a gradient descent technique to find the best fit model for a given data set with the target to achieve minimum integral square error (ISE) between predicted and experiment data. Results The regression results for both ionic liquid dissolution and solid acid saccharification were ISE 107.62 at a computational time of 907.35 s, and ISE 69.65 at 672.90 s, respectively. The high R-squared value of 0.98829 (ionic liquid dissolution) and 0.92585 (solid acid saccharification) indicated the good fit of the models. An optimum reducing sugars yield of 99.0% at dissolution conditions: 1.5 h, 155 degrees C and 1.5% substrate loading; and saccharification conditions: 1.5 h, 120 degrees C and 6% catalyst loading, was achieved. Conclusion This study has demonstrated the good fit of a model for the sequential ionic liquid dissolution-solid acid saccharification process. The model developed has the potential to be used in predicting sugars production in the sequential ionic liquid dissolution-solid acid saccharification. (c) 2018 Society of Chemical Industry