Iterative Data-Driven ${\cal H}_{\infty}$ 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 a 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.

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