Adaptive Unknown Input and State Observers

Adaptive schemes for unknown input and state estimation are proposed for a class of uncertain systems with bounded unknown inputs. First, using a Lyapunov approach, conditions are derived that ensure the state and unknown input estimation errors converge to zero for a constant unknown input. Next, combining a Lyapunov approach and linear matrix inequalities, conditions are given that guarantee a prescribed performance level for state and unknown input estimation for a bounded not necessarily constant unknown input.