Comparative evaluation of nonlinear model predictive and flatness-based two-degree-of-freedom control design in view of industrial application

Two advanced nonlinear model-based control design methods – nonlinear model predictive control (NMPC) and a two-degree-of-freedom control-scheme with flatness-based feedforward control design and decentralised PI-controllers (FB-2DOF) – are compared in view of industrial application. The comparative evaluation is carried out on a setpoint-transition of the Klatt–Engell reactor model. Based on an analysis of simulation scenarios, the controllers are compared with respect to controller performance, robustness criteria, and implementation issues. Thereby, the choice of the control task and the comparison methodology are oriented on industrial practice.In the considered comparative evaluation, NMPC exhibits performance advantages when it comes to time-efficient setpoint-transitions in the nominal case, in which FB-2DOF control design is restricted by the existing input constraints. In return, robustness of stability of the FB-2DOF controller is determined only by the feedback controll part; it is therefore independent from the setpoint-transition performance – determined by the feedforward controll part – whereas the NMPC suffers from degradation of robustness properties if it is tuned for time-efficiency only. NMPC allows direct incorporation of process models and constraints, but, as it employs computationally expensive online optimisation, has to be connected to the digital control system (DCS) via some standard interface. The FB-2DOF controller in contrast can be directly implemented in a DCS, whereby the feedforward-part can be realised as an extension of an already existing feedback-part.