Iterative Data-Driven ℋ∞ Norm Estimation of Multivariable Systems With Application to Robust Active Vibration Isolation

This paper aims to develop a new data-driven H∞ norm estimation algorithm for model-error modeling of multivariable systems. An iterative approach is presented that requires significantly fewer prior assumptions on the true system, hence it provides stronger guarantees in a robust control design. The iterative estimation algorithm is embedded in a robust control design framework with a judiciously selected uncertainty structure to facilitate high control performance. The approach is experimentally implemented on an industrial active vibration isolation system (AVIS).