Nonlinear Model Predictive Control of an Industrial Process with Steadystate Gain Inversion Abstract   Nonlinear model predictive controller (NMPC) is formulated for an industrial process with steadystate gain inversion so that the output variable can be maximized at the peak in presence of disturbances. Appropriate disturbance model formulation is used along with a novel output measurement to allow for robust control in presence of both measured and unmeasured disturbances at the peak where steadystate gain inversion occurs. The constrained nonlinear controller for a process with steadystate gain inversion has been applied successfully with results from plant data that show robustness in maximizing the selectivity of effluent ethylene oxide in the industrial ethylene epoxidation reactor.

Timeminimal set point transition for nonlinear SISO systems under different constraints Abstract   Set point transition of nonlinear plants plays an important role in many applications where dynamic process management has to be considered. This transition should be rapid xe2x80x93 as operation in the new set point increases the economical benefit xe2x80x93 but in compliance with all safety regulations. We present a feedforward approach for a timeminimal set point transition of singleinput, singleoutput nonlinear plants with respect to input, state and output constraints. The conceptual idea is based on the design of an optimization problem utilizing a coordinate change of the plant and a special setup function for the output trajectory. This allows the simultaneous planning of the trajectory and determination of the corresponding control signal. The formulation of the set point transition as an optimization problem provides a flexible design with respect to the integration of inequality constraints. Additional flexibility is provided by the type of setup functions, which permit any adjustment of the output trajectory between the set points. In contrast to other works, we focus on the stationarity of the system output, which allows a faster transition compared to the requirement to reach a steady state of all states. Finally, we present an example from the field of process systems engineering to demonstrate the applicability of the proposed methodology.