CONTROL OF THE TENNESSEE EASTMAN PROCESS USING INPUT-OUTPUT MODELS

This paper presents a case-study where model predictive control is app lied to control a nonlinear, open-loop unstable process called the Ten nessee Eastman Challenge Process. Both the base case and transitions b etween different operating points are considered. The control scheme i s based on an input-output model identified from plant data. The Model Predictive Controller (MPC) controller acts as a supervisory controll er that dictates the setpoints for a lower level PID loop structure. S imulations are presented to illustrate its effectiveness or disturbanc e rejection and setpoint tracking. (C) 1997 Elsevier Science Ltd.