Validation of an Experimentally Derived Uncertainty Model

Abstract

The discrepancies between measurement data and an analytical nominal model for a large gapmagnetic suspension testbed is accounted for by an uncertainty model. The results show that uncertainty bounds corresponding to a combination of additive and diagonal input multiplicative uncertainty can be obtained directly by calculating the smallest norm of the difference between the measured and nominal model response. Use of the identified uncertainty model allowed a strong correlation between design predictions and experimental results. In addition, robust controllers based on the experimentally derived uncertainty model show significant stability and performance improvements over controllers designed with assumed ad hoc uncertainty levels.