On‐line optimization of constrained multivariable chemical processes

A two‐phase approach to the control and operation of complex chemical processes at their optimum operating conditions is presented. The first phase consists of on‐line parameter identification and state estimation of approximate nonlinear dynamic process models using on‐line and off‐line measurements. In the second phase, the optimum operating strategy is determined by integrating and optimizing this identified process model over a selected time horizon into the future. The method is particularly suited to those processes that exhibit slow dynamic responses and are subject to disturbances that have a significant economic impact. Examples include batch chemical reactors, large distillation towers, and processes with significant holdup times such as large fluidized‐bed reactors.