Generation of Linear Dynamic Models From a Digital Nonlinear Simulation

摘要

Presented are the results and methodology used to derive linear models from a nonlinear simu¬lation. It is shown that averaged positive and negative perturbations in the state variables can reduce numerical errors in finite-difference, partial-derivative approximations and, in the con¬trol inputs, can better approximate the system response in both directions about the operating point. Both explicit and implicit formulations are addressed. Linear models are derived for the F100 engine, and comparisons of transients are made with the nonlinear simulation. The problem of startup transients in the nonlinear simulation in making these comparisons is addressed. Also, reduction of the linear models is investigated using the modal and normal techniques. Reduced-order models of the F100 are derived and compared with the full-state models.