Iterative Adaptive Robust Control via Uncertainty Model Unfalsification

Abstract Unfalsification replaces system identification when the intended use of the model is robust control design. Unfalsification results in a family of uncertainty models, all consistent with the data, which tradeoff model uncertainty and disturbance uncertainty. The family of unfalsified models is used in an iterative approach to system identification and robust control design.