Control

One of the largest benefits derived from the modeling effort is the direct application of the model for optimization. Application of the full nonlinear model directly for control is an elegant but immature field. When solution robustness or speed are concerns, linearizations of the model may be practical. Other compromises of the model include eccessive dependence on empirical fomulations. These empirical formulations are generally unreliable during abnormal situations. APMonitor enables the use of empirical, hybrid, and fundamental models directly in control applications.

Real-time Optimization and Control

The largest benefit derived from the modeling effort is the direct application of the model for optimization. Application of the full nonlinear model directly for control is an elegant but immature field. When solution robustness or speed are concerns, linearizations of the model may be practical. Other compromises of the model include eccessive dependence on empirical fomulations. These empirical formulations are generally unreliable during abnormal situations. APMonitor enables the use of empirical, hybrid, and fundamental models directly in control applications.

Nonlinear control adjusts variables that are declared as Manipulated Variables (MVs) to meet an objective. The MVs are the handles that the optimizer uses to minimize an objective function.

The objective is formulated from Controlled Variables (CVs). The CVs may be controlled to a range, a trajectory, maximized, or minimized. The CVs are an expression of the desired outcome for the controller action.

Nonlinear Control

The DBS file parameter imode is used to control the simulation mode. This option is set to 6 for nonlinear control.

NLC.imode = 6