Robust autopilot design strategy for functionally dependent parameter uncertainties

In this paper an approach is presented to incorporate known functional dependencies of model parameters on uncertain physical quantities. The approach is suitable in cases where the source of the plant uncertainty is mainly accountable by a few unknown physical parameters. In such cases, uncertainty over-bounding is greatly reduced compared with using general uncertainty descriptions. This may lead to a better performance/robustness trade-off in a robust controller design. The basis of the approach is to describe the model uncertainties in the unknown physical parameters as linear fractional transformations (LFTs). Then, using LFT algebra, an LFT is obtained, which describes the effect of the uncertain variables on the plant model. The resulting model can be used with several robust control synthesis techniques. In particular, in this paper le synthesis, which is most suitable for the resulting functional dependence model was adopted. As an example, an aircraft controller to follow roil angle commands while keeping the lateral acceleration close to zero was designed. The resulting controller satisfies the specified performance requirements and its superior characteristics are demonstrated by comparison with a controller which was designed using a general uncertainty bounds model. (C) 1998 John Wiley & Sons, Ltd.