Type: Floating Point, Input Default Value: 2.0 Description: Objective function weight on model value

A weighting factor to penalize deviation of current model predictions from prior model predictions. This is used in estimation applications (APM.IMODE=2, 5, or 8) where the penalty from a prior model prediction is a “forgetting factor” that approximates an infinite estimation horizon or favors prior predictions. The infinite estimation horizon approximation is especially useful for systems that have weakly observable or unobservable states. A higher WMODEL can also help to reduce the aggressiveness of the estimator in aligning with the measurements by balancing with a penalty against shifting too far from the prior predictions. The WMODEL value should never be equal to or larger than the WMEAS value for APM.EV_TYPE=1 (l1-norm). A WMODEL value higher than WMEAS will ignore measured values in favor of matching prior model predictions.

See also WMEAS, Estimation Objective Tuning