Abstract This work is focused on the development of a rigorous, model-based approach for the selection of secondary controlled variables as part of a plant-wide control system design methodology. Secondary controlled variables should be easy to measure, easy to control, fast to respond to changes in the input variables, and lead to automatic, indirect control of the primary controlled variables. While much of the work on this subject has been based upon ad hoc approaches, here a systematic three-stage approach is proposed that addresses issues of controllability and economic performance of the control system. The first stage involves the generation of an initial set of candidate secondary controlled variables and the generation of selection constraints that are used to determine if manipulated variables can be used for control of candidate controlled variables. During the second stage, secondary controlled variables are selected to minimize integral absolute errors (IAEs) of the primary controlled variables subject to minimal loop interactions as determined by a relative gain array analysis. Finally, during the third stage, control performance of the secondary controlled variables is evaluated at off-design operations using a nonlinear process model. The proposed approach is then applied, as ongoing work in the application of plant-wide control, to an acid gas removal unit as part of an integrated gasification combined cycle power plant with CO2 capture.