Robust L2-Gain Observation for structured uncertainties: An LMI approach

نویسندگان

  • Benoit Bayon
  • Gérard Scorletti
  • Eric Blanco
چکیده

The robust L2-gain estimation is investigated for general uncertain systems with structured uncertainties. A new estimation structure is introduced: the Augmented-Gain Observer which encompasses both filters and observers and allows robust estimation even for some classes of unstable systems. Our approach is based on a separation of graphs theorem using frequency dependent Integral Quadratic Constraints. We prove that the design of an Augmented-Gain Observer ensuring a robust L2-gain performance can be expressed as a convex optimization problem. This problem involves Linear Matrix Inequalities constraints and can be solved using an efficient algorithm. A numerical example illustrates the interest of the method.

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تاریخ انتشار 2011