| Abstract: | In real-time optimization (RTO), results analysis is used to ensure that RTO predictions can be implemented and are not the result of the unnecessary variance transmission around the RTO loop. Miletic and Marlin [2] proposed a statistical framework for analyzing RTO results; however, their method cannot effectively deal with inequality constraints. Many industrial RTO implementations include bounds on the changes that the RTO system can make to the process operation (i.e. trust-region constraints). Such trust-region constraints can seriously degrade the performance of existing results analysis methods. In this paper, a results analysis procedure is proposed that incorporates statistical testing on both the primal and dual variables of the optimization problem to effectively analyze steady-state RTO results in the presence of trust-region constraints. The proposed method is illustrated using two small case studies, one of which is the same Williams and Otto [11] reactor example used in [2]. |
