On-line steady-state optimisation of nonlinear constrained processes with slow dynamics

Abstract

A scheme for on-line optimisation of constrained nonlinear processes with slow dynamics is suggested and applied to a continuous reactor process. A two-model adaptive mechanism, dynamic and steady state, is used in the scheme. The dynamic model is used to approximate the process locally at each working point for the purpose of estimating steady-state derivatives, and the steady-state model is used for model-based optimisation. The performance lost caused by the inaccuracy of the steady-state model is compensated for by derivatives information which is obtained from dynamic data. The correct optimum can be achieved on-line even if both models are very rough. As shown in applications, the scheme is suited to various types of constraints and nonlinearities and is noise-insensitive.