On asymptotically reconstructing local-state trajectories for 2-D systems without exploiting input information

Abstract

The notions of input-containing and detectability subspaces are developed within the context of observer synthesisfor two-dimensional (2-D) Fornasini-Marchesini models. Specifically, the paper considers observers which asymptotically estimate the local state, in the sense that the error tends to zero as the reconstructed local state evolves away from possibly mismatched boundary values, modulo a detectability subspace. Ultimately, the synthesis of such observers in the absence of explicit input information is addressed.