Controlled-Variable Selection based on Chaos Theory for the Tennessee Eastman Plant

Abstract

This work explores a link between chaotic signals and the selection ofcontrolled variables for plantwide control system design. Some results areshown for the Tennessee Eastman plant, which is well-known for being achallenging process in the field of plant-wide control. This article provides asystematic, data-driven method to select which variables should be controlled.However, since plantwide control problems are inherently complex, this workdoes not intend to provide a definite solution, but a complementary analysis totake into account towards the final control system design. The discussionhighlights the potential hidden in the chaos theory to reduce the complexity ofthe resulting control system.