Control of Steady-state Gradient of an Ammonia Reactor using Transient Measurements

Abstract

This paper presents the application of a steady-state real-time optimization strategy using transient measurements to an ammonia synthesis reactor case. We apply a new method for estimating the steady-state gradient of the cost function based on linearizing a dynamic model at the present operating point. The gradient is controlled to zero using a standard feedback controller, for example, a PI-controller. The applied method is able to adjust fast to the new optimal operation in case of disturbances. The advantage compared to standard steady-state real-time optimization is that it reaches the optimum much faster and without the need to wait for steady-state to update the model. It is significantly faster than classical extremum-seeking control and does not require the measurement of the cost function and additional process excitation. Compared to self-optimizing control, it allows the process to achieve the true optimum.