In this paper, a robust decision-making strategy for integration of design and control under uncertainty is developed for multiple steady-state processes. The major challenge in the integration of design and control is the presence of disturbances and process uncertainty, particularly in the nonlinear process with multiple steady states. A fuzzy model is used as a surrogate model to reduce computational loading in a large operating scope in this work. Based on fuzzy model rules, a robust PI controller design using linear matrix inequalities is developed to guarantee the disturbance rejection performance, stability, and robustness. Finally, through an illustrative process with multiplicity behaviors, the features of the proposed method are demonstrated. Comparisons between the proposed method and the conventional sequential approach are made. The resulting design shows that the proposed method under the designed process with uncertainty would gain more profits than the past design approaches. (C) 2019 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.