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

Benoit Bayon (1) , Gérard Scorletti (1) , Eric Blanco (1)

1 AMPERE - Ampère

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.

Domaines: Automatique / Robotique

Benoit Bayon, Gérard Scorletti, Eric Blanco. Robust L2-Gain Observation for structured uncertainties: An LMI approach. 50th IEEE CDC - ECC, Dec 2011, Orlando, FL, United States. pp.4949-4954, ⟨10.1109/CDC.2011.6160797⟩. ⟨hal-00655803⟩