Self-optimizing control with active set changes

Abstract

In this paper we extend the “nullspace method” by [1] to cover changes in active set. The extension is based on recent results from explicit model predictive control by [3]. The nullspace method is a method for selecting controlled variables, assuming that the set of active constraints does not change. With the extension presented here, we show that by applying the nullspace method for several different regions, where the regions are found by a parametric program, we can use the value of the controlled variables for each region to decide when to switch regions.The proposed method is demonstrated on a simple model of an ammonia production plant, and the results are comparable to real-time optimization.